Type: Article
Aguilera, Ana M., Gutiérrez, Ramón, Ocaña, Francisco A.
and Valderrama, Mariano J. (1995)
Computational approaches to estimation in the Principal
Component Analysis of a stochastic process,
Applied Stochastic Models and Data Analysis,
Vol. 11, pp. 279-299.
DOI: 10.1002/asm.3150110402
[
ZMATH]
[
CrossRef]
Abstract:
After performing a review of the classical procedures for estimation
in the principal component analysis (PCA) of a second order stochastic process,
two alternative procedures have been developed to approach such estimates.
The first is based on the orthogonal projection method and uses cubic interpolating
splines when the data are discrete. The second is based on the trapezoidal method.
The accuracy of both procedures is tested by simulating approximated sample-functions
of the Brownian motion and the Brownian bridge. The real principal factors of these
stochastic processes, which can be evaluated directly, are compared with those
estimated by means of the two mentioned algorithms. An application for estimation
in the PCA of tourism evolution in Spain from real data is also included.
Keywords:
principal components; Karhunen-Loève expansion; orthogonal projection;
trapezoidal algorithm; Brownian motion; Brownian bridge.
@ARTICLE{Aguilera:etal:95,
author = "Ana M. Aguilera and Ram{\'o}n Guti{\'e}rrez and
Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1995",
title = "Computational approaches to estimation in the {P}rincipal
{C}omponent {A}nalysis of a stochastic process",
journal = "Applied Stochastic Models \& Data Analysis",
volume = "11",
pages = "279--299",
doi = "10.1002/asm.3150110402",
}
Type: Article
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1996),
Análisis en Componentes Principales de un proceso con
funciones muestrales escalonadas,
Questiio,
Vol. 20, No. 1, pp. 7-28.
[
CINDOC]
[
PDF Full text]
[
Dialnet]
[
UPCommons]
Abstract:
El ACP de un número finito de variables puede ser generalizado
para manejar datos que evolucionan en el tiempo. El objetivo de
este trabajo es la estimación de los factores principales de
procesos aleatorios con funciones muestrales escalonadas. Ante la
imposibilidad de obtener una solución exacta a este problema, se
propone estimar el ACP de un proceso de este tipo a partir del ACP
del proceso cuyas trayectorias se obtienen como proyección de
las originales en el subespacio de las funciones constantes sobre
los subintervalos de una partición previamente fijada.
Finalmente, se incluye una aplicación con datos reales
(nombramientos de Profesores Titulares de Universidad en 1992)
estudiando el error cuadrático medio de las reconstrucciones del
proceso proporcionadas por el ACP así aproximado.
Keywords: operador de covarianza, componentes
principales, autovalores y autofunciones, proyección ortogonal.
@ARTICLE{Aguilera:etal:96Quest,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1996",
title = "{ACP} de un proceso estoc{\'a}stico con funciones muestrales
escalonadas",
journal = "Q{\"u}estii{\`o}",
volume = "20",
pages = "7--28",
}
Type: Article
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1997),
An approximated Principal Component Prediction model for continuous
time stochastic processes,
Applied Stochastic Models and Data Analysis,
Vol. 13, pp. 61-72.
DOI: 10.1002/(SICI)1099-0747(199706)13:2<61::AID-ASM296>3.0.CO;2-I
[
ZMATH]
[
CrossRef]
Abstract:
In this paper, a linear model for forecasting a continuous-time stochastic
process in a future interval in terms of its evolution in a past interval
is developed. This model is based on linear regression of the principal
components in the future against the principal components in the past.
In order to approximate the principal factors from discrete observations of a
set of regular sample paths, cubic spline interpolation is used.
An application for forecasting tourism evolution in Granada is also included.
Keywords:
Principal components; Karhunen-Loève expansion;
least squares linear prediction; cubic B-splines.
@ARTICLE{Aguilera:etal:97PCP,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1997",
title = "An Approximated {P}rincipal {C}omponent {P}rediction model for continuous
time stochastic processes",
journal = "Applied Stochastic Models \& Data Analysis",
volume = "13",
pages = "61--72",
}
Type: Article
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1997),
Regresión sobre Componentes Principales de un proceso
Estocástico con Funciones Muestrales Escalonadas,
Estadística Española,
Vol. 39, No. 142, pp. 5-21.
[
INE]
[
PDF full text]
[
Dialnet]
Abstract:
El objetivo de este trabajo es desarrollar un procedimiento para
estimar observaciones faltantes de un proceso estocástico con
funciones muestrales escalonadas a partir de su evolución en el
pasado.
El modelo que se propone está basado en regresión lineal
múltiple en términos de las componentes principales asociadas
al proceso en el pasado. Los factores principales de un proceso de
este tipo se aproximan mediante los del proceso cuyas trayectorias
se obtienen como proyección de las del proceso original en el
subespacio de las funciones constantes sobre los subintervalos de
una partición previamente fijada en el pasado. Finalmente, se
incluye una aplicación con datos simulados.
Keywords: función de covarianza; componentes
principales; estimación lineal mínimo cuadrática;
proyección ortogonal; modelo ECP.
@ARTICLE{Aguilera:etal:97RegCP,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1997",
title = "Regresi{\'o}n sobre componentes principales de un proceso estoc{\'a}stico con
funciones muestrales escalonadas",
journal = "Estad{\'{\i}}stica Espa{\~n}ola",
volume = "39",
number = "142",
pages = "5--21",
}
Type: Article
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1999),
Forecasting with unequally spaced data by a functional Principal
Component approach,
Test,
Vol. 8, No. 1, pp. 233-253.
DOI: 10.1007/BF02595871
[
Compressed PDF file]
[
ZMATH]
[
CrossRef]
Abstract:
The Principal Component Regression model of multiple responses is extended to
forecast a continuous-time stochastic process. Orthogonal projection on a
subspace of trigonometric functions is applied in order to estimate the principal
components using discrete-time observations from a sample of regular curves.
The forecasts provided by this approach are compared with classical principal
component regression on simulated data.
Keywords:
Karhunen-Loève expansion; least-squares linear prediction; orthogonal projection;
principal components.
@ARTICLE{Aguilera:etal:99Test,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1999",
title = "Forecasting with unequally spaced data by a functional principal
component approach",
journal = "Test",
volume = "8",
number = "1",
pages = "233--253",
doi = "10.1007/BF02595871",
}
Type: Article
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1999),
Forecasting time series by functional PCA. Discussion of several weighted
approaches,
Computational Statistics,
Vol. 14, No. 3, pp. 443-467.
[
SSRN]
[
CrossRef]
Abstract:
In this paper a functional principal component model is applied to forecast
a continuous time series that has been observed only at discrete time points
not necessarily equally spaced. To take into account the natural order among
the sample paths obtained after cutting the series into pieces, a weighted
estimation of the principal components is proposed. In order to estimate the
weighted functional principal component analysis, a cubic spline interpolation
of the sample paths between their discrete observations is performed.
Finally, an application with stimulated data is developed where model fitting
and forecasting results using different types of weightings on equally and
unequally spaced data are given and discussed. The forecasting performance
of the estimated functional principal component models is also compared with
multivariate principal component regression models.
@ARTICLE{Aguilera:etal:99weight,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1999",
title = "Forecasting time series by functional {PCA}. {D}iscussion of several
weighted approaches",
journal = "Computational Statistics",
volume = "14",
number = "3",
pages = "443--467",
doi = "10.1007/s001800050025",
}
Type: Article
Ocaña, Francisco A., Aguilera, Ana M. and
Valderrama, Mariano J. (1999),
Functional Principal Components Analysis by choice of norm,
Journal of Multivariate Analysis,
Vol. 71, No. 2, pp. 262-276.
DOI: 10.1006/jmva.1999.1844
[
ZMATH]
[
CrossRef]
[
MathSciNet]
Abstract:
The functional principal components analysis (PCA) involves new considerations
on the mechanism of measuring distances (the norm). Some properties arising in
functional framework (e.g., smoothing) could be taken into account through
an inner product in the data space. But this proposed inner product could make,
for example, interpretational or (and) computational abilities worse.
The results obtained in this paper establishes equivalences between the PCA
with the proposed inner product and certain PCA with a given well-suited
inner product. These results have been proved in the theoretical framework
given by Hilbert valued random variables, in which multivariate and functional PCAs
appear jointly as particular cases.
Keywords: functional data analysis; Hilbert space; PCA; smoothing.
@ARTICLE{Ocana:etal:99,
author = "Francisco A. Oca{\~n}a and Ana M. Aguilera and Mariano J. Valderrama",
year = "1999",
title = "Functional principal component analysis by choice of norm",
journal = "Journal of Multivariate Analysis",
volume = "71",
number = "2",
pages = "262--276",
doi = "10.1006/jmva.1999.1844",
}
Type: Article
Aguilera, Ana M., Ocaña, Francisco A. and Valderrama, Mariano J. (1999),
Stochastic modelling for evolution of stock prices by means of functional PCA,
Applied Stochastic Models in Business and Industry,
Vol. 15, No. 4, pp. 227-234.
DOI: 10.1002/(SICI)1526-4025(199910/12)15:4<227::AID-ASMB388>3.0.CO;2-C
[
ZMATH]
[
CrossRef]
Abstract:
The objective of this paper is to apply functional principal component analysis
to model and forecast financial prices of the banking in Madrid Stock Market from
weekly observations of a random sample of banks. It is well known that direct
statistical analysis of stock prices is difficult, therefore principal
component prediction models for weekly returns are performed to give
appropriate forecasts for prices.
Keywords:
functional data; principal components; least-squares linear prediction;
interpolating splines; weekly returns.
@ARTICLE{Aguilera:etal:99prices,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1999",
title = "Stochastic modelling for evolution of stock prices
by means of functional {PCA}",
journal = "Applied Stochastic Models in Business and Industry",
volume = "15",
number = "4",
pages = "227--234",
}
Type: Article
Ocaña, Francisco A., Aguilera, Ana M. and
Escabias, Manuel (2007),
Computational Considerations in Functional Principal
Component Analysis,
Computational Statistics,
Vol. 22, No. 3, pp. 449-465.
DOI: 10.1007/s00180-007-0051-2
[
CrossRef]
Abstract:
Computing estimates in functional principal component analysis
(FPCA) from discrete data is usually based on the approximation of
sample curves in terms of a basis (splines, wavelets, trigonometric
functions, etc.) and a geometrical structure in the data space
(L2 spaces, Sobolev spaces, etc.). Until now, the computational
efforts have been focused in developing ad hoc algorithms to
approximate those estimates by previously selecting an efficient
approximating technique and a convenient geometrical structure. The
main goal of this paper consists of establishing a procedure to
formulate the algorithm for computing estimates of FPCA under
general settings. The resulting algorithm is based on the classic
multivariate PCA of a certain random vector and can thus be
implemented in the majority of statistical packages. In fact, it is
derived from the analysis of the effects of modifying the norm in
the space of coordinates. Finally, an application on real data will
be developed to illustrate the so derived theoretic results.
Keywords:
Functional data analysis; Hilbert spaces; Principal components;
Covariance estimation; Orthogonal projection.
@ARTICLE{Ocana:col07:compuFPCA,
author = "Francisco A. Oca{\~n}a and Ana M. Aguilera and
Manuel Escabias",
year = "2007",
title = "Computational Considerations in Functional Principal Component Analysis",
journal = "Computational Statistics",
volume = "22",
number = "3",
pages = "449--465",
doi = "10.1007/s00180-007-0051-2",
}
@ARTICLE{Ocana07:aproxVolat,
author = "Francisco A. Oca{\~n}a",
year = "2007",
title = "An approximation problem in computing electoral volatility",
journal = "Applied Mathematics and Computation",
volume = "192",
number = "2",
pages = "299--310",
doi = "10.1016/j.amc.2007.03.032",
}
Type: Article
Mariano J. Valderrama, Francisco A. Ocaña, Ana M. Aguilera y
Francisco M. Ocaña-Peinado (2010; Epub. 2009),
Forecasting pollen concentration by a two-step functional Model,
Biometrics, Vol. 66, No. 2, pp. 578-585.
DOI: 10.1111/j.1541-0420.2009.01293.x
[
CrossRef]
Abstract:
A functional regression model to forecast the cypress pollen
concentration during a given time interval, considering the air
temperature in a previous interval as the input, is derived by means
of a two--step procedure. This estimation is carried out by functional
principal component analysis and the residual noise is also modelled
by functional principal component regression, taking as the
explicative process the pollen concentration during the earlier
interval. The prediction performance is then tested on pollen data
series recorded in Granada (Spain) over a period of ten years.
Keywords:
Functional linear regression; Karhunen-Loève expansion;
Pollen concentration; Transfer function model.
@ARTICLE{Valderrama:etal09:pollen,
author = "Mariano J. Valderrama and Francisco A. Oca{\~n}a and
Ana M. Aguilera and Francisco M. Oca\~na--Peinado",
year = "2010",
title = "Forecasting Pollen Concentration by a Two--Step Functional Model",
journal = "Biometrics",
doi = "10.1111/j.1541-0420.2009.01293.x",
}
Type: Article
Ocaña, Francisco A. and Oñate, Pablo (2011),
IndElec: A Software for Analyzing Party Systems and Electoral Systems,
Journal of Statistical Software, Vol. 42, No. 6, pp. 1-28.
[Journal link]
Abstract
IndElec is a software developed to compute a wide range of indices
from electoral data. Such indices are indented to analyze both party
systems and electoral systems in political studies.
Further, IndElec can calculate such indices from electoral data at several levels of
aggregation, even when the acronyms of some political parties change
across districts. As the amount of information provided by IndElec
may be considerable, it also aids the user in the analysis of such
information through three capabilities.
First, IndElec automatically elaborates preliminary
descriptive statistical reports of computed indices.
Second, IndElec saves the computed information into text files in data
matrix format, which can be directly loaded by any statistical
software to facilitate more sophisticated statistical studies.
Third, IndElec provides results in
several file formats (Text, CSV, HTML, R)
to facilitate their visualization and management
by using a wide range of application softwares
(word processors, spreadsheets, web browsers, etc.).
Finally, a GUI is provided for IndElec,
but no result is shown in this environment.
In fact, both the input and output for IndElec
are arranged in files with the aforementioned formats.
Keywords:
electoral system, disproportionality, party
system, party dimensions.
@ARTICLE{OcanaOnate11:soft:indelec,
author = "Francisco A. Oca{\~n}a and Pablo O{\~n}ate",
year = "2011",
title = "{IndElec}: A Software for Analyzing Party Systems and Electoral
Systems",
journal = "Journal of Statistical Software",
volume = "42",
number = "6",
pages = "1--28",
url = "http://www.jstatsoft.org/v42/i06/",
}
Type: Article
Aguilera, Ana M., Escabias, Manuel, Ocaña, Francisco A., and
Valderrama, Mariano J. (2015),
Functional wavelet-based modelling of dependence between lupus and stress,
Methodology and Computing in Applied Probability,
Vol. 17, No. 4, pp. 1015-1028.
DOI: 10.1007/s11009-014-9424-5
[
CrossRef]
Abstract:
The power of functional linear regression to estimate a set of curves from others involved is studied in this work in the context of life sciences. The objective is to determine the relationship between the degree of lupus and the level of stress for patients suffering this autoimmune disease. Daily stress and lupus curves have a strong local behavior with missing data those days that a patient does not answer the corresponding test. Because of this, wavelet smoothing with an appropriate thresholding rule is considered. Then, functional principal component analysis of the response and predictor variables is used to reduce the dimension and solve the multicollinearity problem that affects the estimation of the functional linear regression model with functional response. Model selection is solved by using a criterion that selects those pairs of response/predictor components that explain the highest proportions of response variability. The performance of the proposed functional model is tested on simulated and real data.
Keywords:
Functional regression, Functional PCA, Wavelet approximation, Lupus.
@ARTICLE{AguileraEtalLupus2015,
author = "Ana M. Aguilera and Manuel Escabias and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "2015",
title = "Functional wavelet--based modelling of dependence between lupus and stress",
journal = "Methodology and Computing in Applied Probability",
volume = "17",
number = "4",
pages = "1015--1028",
doi = "10.1007/s11009-014-9424-5",
}
Type: Article
Arrebola, M. L., Navarro, M. C., Jiménez, J. and
Ocaña, F. A. (1994),
Variations in yield and composition
of the essential oil of Satureja Obovata,
Phytochemistry,
Vol. 35, No. 1, pp. 83-93.
[
CrossRef]
Abstract:
The difference in yield and composition of the essential oil of
Satureja obovata (‘savory’) has been investigated.
The research included all of its different phonological stages,
in several populations of the provinces of Granada and Málaga,
during three consecutive years. Quantitative analysis of the essential
oil revealed the existence of two distinct groups of samples depending
on their major components: (i) oxygenated monoterpenic derivatives and
(ii) aromatic alcohols and their precursors.
@ARTICLE{Arrebola:94:SO,
author = "M. L. Arrebola and M. C. Navarro and J. Jim{\'e}nez and
F. A. Oca{\~n}a",
year = "1994",
title = "Variations in yield and composition of the essential oil
of {S}atureja {O}bovata",
journal = "Phytochemistry",
volume = "35",
number = "1",
pages = "83--93",
doi = "10.1016/S0031-9422(00)90514-4",
}
Type: Article
Arrebola, M. L., Navarro, M. C., Jiménez, J. and
Ocaña, F. A. (1994),
Yield and composition of the
essential oil of Thymus Serpylloides Subsp. Serpylloides,
Phytochemistry,
Vol. 36, No. 1, pp. 67-72, 1994.
[
CrossRef]
Abstract
The difference in yield and composition of essential oil of
Thymus serpylloides subsp. serpylloides (‘thyme of the Sierra’)
has been investigated. The research included all of its different
phonological stages, its sexual characteristics,
during three consecutive years. Quantitative analysis of the essential
oil revealed that there is a predominance of both aromatic alcohols
(carvacrol being the most abundant component in this group) and their
precursors (g-terpinene and p-cymene).
@ARTICLE{Arrebola:94:TS,
author = "M. L. Arrebola and M. C. Navarro and J. Jim{\'e}nez and
F. A. Oca{\~n}a",
year = "1994",
title = "Yield and composition of the essential oil of {T}hymus {S}erpylloides
{S}ubsp. {S}erpylloides",
journal = "Phytochemistry",
volume = "36",
number = "1",
pages = "67--72",
doi = "10.1016/S0031-9422(00)97014-6",
}
Type: Article
Ocaña, Francisco A., Valderrama, Mariano J., Aguilera, Ana M. and
Gutiérrez-Jáimez, R. (1995),
Repercusión económica en Granada
de los estudiantes universitarios foráneos,
Ars Pharmaceutica,
Vol. 36, No. 1, pp. 59-71.
Abstract:
En este artículo se analiza la distribución del gasto de los
alumnos foráneos de la Universidad de Granada en conceptos tales
como manutención, ocio, etc., en términos de su forma de
residencia en la ciudad de Granada. Asimismo se evalúa la
repercusión de este colectivo en la economía granadina.
@ARTICLE{Ocana:etal:95,
author = "F. A. Oca{\~n}a and M. J. Valderrama and A. M. Aguilera and
R. Guti{\'e}rrez-J{\'a}imez",
year = "1995",
title = "Repercusi{\'o}n econ{\'o}mica en {G}ranada de los estudiantes
universitarios for{\'a}neos",
journal = "Ars Pharmaceutica",
volume = "36",
number = "1",
pages = "59--71",
}
Type: Article
Ocaña, Francisco A. and Oñate, Pablo (1999),
Índices e Indicadores del sistema
electoral y del sistema de partidos. Una propuesta informática
para su cálculo,
REIS(Revista Española de Investigaciones Sociológicas),
No. 86, pp. 223-245.
[
Journal Link]
[
DIALNET]
[
JSTOR]
Abstract:
En este artículo se hace una breve revisión de las medidas que
cuantifican distintas características de los sistemas de partidos
políticos (dimensiones del voto) y de las que miden la
distorsión entre las distribuciones de voto y escaños debida a
la acción del sistema electoral (desproporcionalidad).
Asimismo, este artículo tiene por objeto presentar el programa
computacional IndElec, desarrollado por los autores, que
permite obtener los indicadores m´s importantes. Dicho programa
es aplicado a los resultados de las elecciones al Congreso de los
Diputados celebradas en España desde 1977 hasta la fecha. Los
resultados obtenidos por IndElec ilustran el comportamiento
de los indicadores anteriormente mencionados en el caso de las
Elecciones Generales.
@ARTICLE{Ocana:Onate99,
author = "Francisco A. Oca{\~n}a and Pablo O{\~n}ate",
year = "1999",
title = "{\'I}ndices e indicadores del sistema electoral y del sistema de partidos.
{U}na propuesta inform{\'a}tica para su c{\'a}lculo",
journal = "Revista Espa{\~n}ola de Investigaciones Sociol{\'o}gicas",
volume = "86",
pages = "223--245",
}
Type: Article
Ocaña, Francisco A. and Oñate, Pablo (2000),
Las elecciones autonómicas de 1999 y las Españas
electorales,
REIS (Revista Española de Investigaciones Sociológicas),
No. 90, pp. 183-228.
[
Journal Link]
[
DIALNET]
[
JSTOR]
Abstract:
En este artículo se estudian las principales características de
los sistemas y subsistemas de partidos surgidos de la última
convocatoria electoral de carácter autonómico. Se analizan los
datos que en cada Comunidad Autónoma alcanzan la fragmentación, el
número de partidos, la concentración, la competitividad, la
polarización y la volatilidad, y se comparan con los valores que
estas dimensiones alcanzan en otras Comunidades Autónomas, así
como con los registrados en anteriores convocatorias. En la
conclusión se señalan los distintos sistemas y subsistemas, modelo
general y excéntricos, que pueden distinguirse en atención a las
respectivas características de las pautas de la competición
partidista y electoral en estas plurales arenas electorales.
@ARTICLE{Ocana:Onate00,
author = "Francisco A. Oca{\~n}a and Pablo O{\~n}ate",
year = "2000",
title = "Las elecciones auton{\'o}micas de 1999 y las {E}spa{\~n}as electorales",
journal = "Revista Espa{\~n}ola de Investigaciones Sociol{\'o}gicas",
volume = "90",
pages = "183--228",
}
Type: Article
Oñate, Pablo and Ocaña, Francisco A. (2000),
Elecciones de 2000 y sistemas de partidos en España:
¿ cuánto cambio electoral?,
Revista de Estudios Políticos,
No. 110, 297-336.
[
Journal Link]
[
DIALNET]
Abstract:
En este artículo se analizan los cambios producidos en las
Elecciones Generales del 2000. Se lleva a cabo un análisis de la
configuración de los subsistemas de partidos en términos de las
dimensiones del voto y de la desproporcionalidad. Además, se
analiza, de forma cuantitativa y a la luz de los datos
electorales, la afirmación por la que se justificaba la victoria
del Partido Popular a partir de la alta presencia de la abstención
en el voto.
@ARTICLE{Onate:Ocana00,
author = "Pablo O{\~n}ate and Francisco A. Oca{\~n}a",
year = "2000",
title = "Elecciones de 2000 y sistemas de partidos en {E}spa{\~n}a:
{?`}cu{\'a}nto cambio electoral?",
journal = "Revista de Estudios Pol{\'{\i}}ticos",
volume = "110",
pages = "297--336",
}
Type: Article
Talavera, Eva M., Guerrero, Pablo, Ocaña, Francisco A. and
Álvarez-Pez, José M. (2002),
Photophysical and Direct Determination of Binding Constants of Ethidium
Bromide complexed to E. coli DNA,
Applied Spectroscopy,
Vol. 56, No. 3, pp. 362-369.
DOI: 10.1366/0003702021954737
[
IngentaConnect]
[
CrossRef]
Abstract:
High precision time-correlated single photon counting data were
obtained to achieve the resolution of the fluorescence decay time
components from DNA-Ethydium bromide (Eb) buffered solutions at
low (0.05 M) and high (0.4 M) NaCl concentrations.
Tri-exponential functions are the best models to describe the
decay kinetics in all solutions, independently of the NaCl
concentration. The fluorescence nanosecond graphs were recorded
intercalating polarizers into path-light to check for anisotropy
artifacts. The results suggest that the three exponentials from
fluorescence decay graphs depict three true lifetimes, which, in
general, are dependent on the [DNA]/[Eb] ratio and can be
assigned to free Eb and bound Eb at the low- and high-affinity
DNA sites. With the normalized weighting coefficients from
tri-exponential fitting of nanosecond decay graphs, recorded at
the excitation wavelength of the isosbestic point, it has been
possible to calculate the values of binding constants and sites
number at the two salt concentrations by means of the neighbor
exclusion model (McGhee-von Hippel expression).
@ARTICLE{Talavera02etal:scat,
author = "Eva M. Talavera and Pablo Guerrero and Francisco A. Oca{\~n}a and
Jos{\'e} M. {\'A}lvarez--{P}ez",
year = "2002",
title = "Photophysical and Direct Determination of Binding Constants of
{E}thidium {B}romide complexed to {E.} coli {DNA}",
journal = "Applied Spectroscopy",
volume = "56",
number = "3",
pages = "362--369",
doi = "10.1366/0003702021954737",
}
Type: Article
Oñate, Pablo and Ocaña, Francisco A. (2005),
Las elecciones generales de marzo de 2004 y
los sistemas de partidos en España: ¿Tanto cambio electoral?
Revista Española de Ciencia Política,
No. 13, pp. 159-182.
[
Journal Link]
[
DIALNET]
Abstract:
En este artículo se analizan los efectos de los resultados de las
elecciones generales de marzo de 2004 sobre los sistemas de partidos
en España, a la luz de las dimensiones del voto o del sistema de
partidos. Dadas las especiales circunstancias que rodearon esta
convocatoria, nuestro objetivo será comprobar la medida en la que se
ha dado un cambio electoral y si debemos hablar de elecciones de
continuidad o elecciones excepcionales, como recomendarían las
circunstancias que contextualizaron la convocatoria de 2004. Con el
necesario apoyo empírico, se intentará dar respuesta a los
siguientes interrogantes: ¿estamos todavía en el tercer período
electoral o estas elecciones abren un nuevo período electoral? ¿Se
sigue dando la excepcionalidad española -y en qué forma- en cuanto a
los plurales y simultáneos sistemas de partidos (común y
excéntricos)? ¿Cuál es el calado del cambio electoral registrado en
las elecciones de 2004: de simple distribución del voto o es más
profundo, al afectar a los alineamientos políticos de los electores?
En función de todo ello, ¿debemos hablar de elecciones de
continuidad o de elecciones excepcionales?
@ARTICLE{Onate:Ocana05:marzo4,
author = "Pablo O{\~n}ate and Francisco A. Oca{\~n}a",
year = "2005",
title = "Las elecciones generales de marzo de 2004 y
los sistemas de partidos en {E}spa{\~n}a: {?`}{T}anto cambio electoral?",
journal = "Revista {E}spa{\~n}ola de Ciencia Pol{\'{\i}}tica",
volume = "13",
pages = "159--182",
}
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1995),
Predicción dinámica de un proceso
estocástico mediante Análisis en Componentes Principales.
Actas de la I Reunión Nacional de Predicción
Dinámica (M.J. Valderrama, ed.), pp. 197-213,
Universidad de Granada, Granada.
@INPROCEEDINGS{Aguilera:etal94:Granada,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1995",
title = "Predicci{\~o}n din{\'a}mica de un proceso estoc{\'a}stico mediante
an{\'a}lisis en componentes principales",
booktitle = "Actas de la I Reuni{\'o}n de Trabajo en Predicci{\'o}n Din{\'a}mica",
editor = "Mariano J. Valderrama",
pages = "1--10",
}
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1995),
A dynamic forecasting model for evolution of Tourism.
Proceedings of 7th International Symposium on ASMDA
(J. Janssen and S. McClean, eds.), pp. 1-10,
University of Ulster.
@INPROCEEDINGS{Aguilera:etal95:asmda,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1995",
title = "A dynamic forecasting model for evolution of tourism",
booktitle = "Proceedings of 7th International Symposium on ASMDA",
editor = "J. Janssen and S. Mc{C}lean",
publisher = "University of Ulster",
volume = "I",
pages = "1--10",
}
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (1996),
On a weighted Principal Component
model to forecast a continuous time series.
Proceedings in COMPSTAT'96 (A. Prat, ed.), pp. 169-174,
Physica-Verlag, Berlin.
@INPROCEEDINGS{Aguilera:col96:PCAw:predi:ts,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "1996",
title = "On a Weighted Principal Component Model to Forecast a Continuous Time Series",
booktitle = "Proceedings in Computational Statistics",
editor = "A. Prat",
publisher = "Physica--Verlag",
address = "Berlin",
pages = "169--174",
}
Ocaña, Francisco A., Valenzuela, Olga and Aguilera, Ana M. (1998),
A wavelet approach to functional
Principal Component Analysis.
Proceedings in COMPSTAT'98 (R. Payne and P. Green, eds.), pp. 413-418,
Physica-Verlag, Berlin.
@INPROCEEDINGS{Ocana:col98:wav:FPCA,
author = "Francisco A. Oca{\~n}a and Olga Valenzuela and Ana M. Aguilera",
year = "1998",
title = "A Wavelet Approach to Functional Principal Component Analysis",
booktitle = "Proceedings in Computational Statistics",
editor = "R. Payne and P. Green",
publisher = "Physica--Verlag",
address = "Berlin",
pages = "413--418",
}
Valderrama, Mariano J., Ocaña, Francisco A. and
Aguilera, Ana M. (2002),
Forecasting PC-ARIMA Models for
Functional Data.
Proceedings in COMPSTAT'2002 (W. Härdle and B. Rönz, eds.), pp. 25-36,
Physica-Verlag, Heidelberg.
@INPROCEEDINGS{Valderrama:col02:PC:ARIMA,
author = "Mariano J. Valderrama and Francisco A. Oca{\~n}a and Ana M. Aguilera",
year = "2002",
title = "Forecasting {PC}--{ARIMA} Models for Functional Data",
booktitle = "Proceedings in Computational Statistics",
editor = "W. H{\"a}rdle and B. R{\"o}nz",
publisher = "Physica--Verlag",
address = "Heidelberg",
pages = "25--36",
}
Aguilera, Ana M., Ocaña, Francisco A. and
Valderrama, Mariano J. (2008),
Estimation of functional regression models for functional
responses by wavelet approximation.
Functional and Operatorial Statistics, Constributions to Statistics Series
(Dabo-Niang, Sophie and Ferraty, Frédéric, eds.), pp. 7-14,
Physica-Verlag, Berlin.
DOI: 10.1007/978-3-7908-2062-1_3
[
CrossRef]
Abstract:
A linear regression model to estimate a sample of response curves
(realizations of a functional response) from a sample of predictor
curves (functional predictor) is considered. Difierent procedures
for estimating the parameter function of the model based on wavelets
expansions and functional principal component decomposition of both
the predictor and response curves are proposed. Wavelets coeficients
will be estimated from discrete observations of sample curves at irregularly
spaced time points that could be difierent among sample individuals.
@INCOLLECTION{Aguilera:iwfos08,
author = "Ana M. Aguilera and Francisco A. Oca{\~n}a and Mariano J. Valderrama",
year = "2008",
title = "Estimation of functional regression models for functional responses
by wavelet approximation",
booktitle = "Functional and Operatorial Statistics",
series = "Contributions to Statistics",
editor = "Sophie Dabo--Niang and Fr{\'e}d{\'e}ric Ferraty",
publisher = "Physica--Verlag",
address = "Berlin",
pages = "7--14",
doi = "10.1007/978-3-7908-2062-1_3",
}
Pablo Oñate y Francisco A. Ocaña (1999),
Análisis de datos electorales.
Serie Cuadernos Metodológicos (No. 27),
Centro de Investigaciones Sociológicas, Madrid.
ISBN 13: 978-84-7476-281-5
ISBN 10: 84-7476-281-2
[
Publisher Link] (Open access available)
Abstract
En este libro se analiza el sistema electoral y los sistemas de
partidos en España a distintos niveles, nacional, autonómico y
distrito electoral. Asimismo, describe detalladamente el programa
IndElec que permite calcular de forma rápida y fiable
índices electorales. El estudio llevado a cabo est´ basado en
los cálculos realizados por IndElec en todas las
elecciones en España celebradas en España hasta la fecha
(generales, autonómicas y europeas) a partir de los datos
oficiales suministrados tanto por el Ministerio del Interio como
por los correspondientes organismos oficiales de las Comunidades
Autónomas. Incluye un análisis comparativo por Comunidades
Autónomas, y por distritos electorales.
@BOOK{OnateOcana99:AnalDatoElec,
author = "Pablo O{\~n}ate and Francisco A. Oca{\~n}a",
year = "1999",
title = "An{\'a}lisis de datos electorales",
series = "Cuadernos Metodol{\'o}gicos",
volume = "27",
publisher = "Centro de Investigaciones Sociol{\'o}gicas",
address = "Madrid",
isbn = "9788474762815",
}
Valderrama, Mariano J., Aguilera, Ana M. and
Ocaña, Francisco A. (2000),
Predicción dinámica mediante análisis de datos
funcionales,
Hespérides-La Muralla, Madrid.
ISBN 13: 978-84-7133-701-6
ISBN 10: 84-7133-701-0
Abstract:
Uno de los objetivos de este libro es dirigir la atención del
lector al problema que constituye la modelización matemática de
magnitudes que evolucionan de forma continua (por ejemplo,
respecto al tiempo), al margen de que su observación se lleve a
cabo de forma discreta (por ejemplo, en un número determinado de
instantes).
En este libro se muestran los resultados básicos del enfoque
basado en componentes principales funcionales para la modelización
de datos funcionales, algunos de ellos obtenidos por los propios
autores. Se aborda el problema de la predicción de forma continua
de datos de naturaleza funcional, incluyendo el caso en el que tan
sólo se dispongan de un conjunto finito de observaciones.
@BOOK{Valderrama:etal:00,
author = "Mariano J. Valderrama and Ana M. Aguilera and Francisco A. Oca{\~n}a",
year = "2000",
title = "Predicci{\'o}n Din{\'a}mica mediante An{\'a}lisis de Datos
Funcionales",
publisher = "La Muralla--Hesp{\'e}rides",
series = "Cuadernos de Estad{\'{\i}}stica",
address = "Madrid",
}
ARIMAp
This software is devoted to the teaching of ARIMA methodology for
time series analysis. It simulates a finite number of observations for a time series
whose ARIMA model has been chosen by the user. This software makes up an
interesting tool in the training stage where the student has to developed
abilities for recognising ARIMA structures from data series.
SMCP2
(Sistema de Modelización
en Componentes Principales de Procesos, in Spanish, and
System for Principal Component Modelling of
Process, in English)
This software carries out all the computations involved in the modelling stage
of a continuous time
stochastic process based on the functional Principal Component approach.
IndElec
This is a software
intended to computing
some measures involved in the study of party and election systems.
It makes possible to
calculate the most important rates of disproportionality in
election systems, and the most widespread dimensions of the party
systems.
wScatFit
This is a software intended to estimating the parameters of the
generalized Scatchard equation (McGhee, J.D. and P.H. von Hippel (1974), J. Mol.
Biol., pp.478).
This equation leads to model several non-cooperativity interacting
ligand-lattice systems.
Mail to Francisco A. Ocaña
Francisco A. Ocaña-Lara