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SDB–Project |
Semiparametric and
distance-based methodologies with applications to bioinformatics, finance and
risk management |
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Summary: The center (of gravity) of this
project is the study of a collection of statistical methods, among which
distance based ones play a predominant role. Their main characteristics are: 1)
They originate in the need to supply solutions to
problems arising in quite diverse scientific disciplines, ranging from
Medicine or Sociology to Actuarial or Financial Risk Management. 2)
They are capable of handling large or huge datasets,
heterogeneous data from several information sources and possibly having a
partially or totally non numeric nature (e.g., functional data, financial
series, DNA sequences). 3)
They take advantage of concepts from Classical or
Bayesian Statistics together with resources from Machine Learning, which
prompts us to name them Semiparametric
Methods. The balanced
theoretical and practical orientation of this research facilitates transfer
of its results to application areas. |
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Research topics: Distance-Based Methods, Goodness-of-fit, Semiparametric Methods for Volatility Models |
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Research team: Universidad
Carlos III de Madrid |
Universitat
de Barcelona |
Inst.
Català d’Oncologia |
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Recent contributions (international journals
only): [1]
Albarrán,
I., Alonso, P.J. and Marin, J.M.
(2011) Non-linear models of disability and age applied to Census Data. Journal of Applied
Statistics, 38, 10, p. 2151-2163. [2]
Arribas-Gil, A. and Romo, J. (2012) Robust
depth-based estimation in the time warping problem. Biostatistics,13 (3), 398-414. on-line version http://biostatistics.oxfordjournals.org/content/early/2011/11/03/biostatistics.kxr037.short?rss=1) [3]
Arribas-Gil, A. and Matias, C. (2012) A context dependent pair hidden Markov
model for statistical alignment. Statistical Applications in Genetics and
Molecular Biology, 11(1), 1-29. [4] Batista-Foguet, J.M., Fortiana, J., Currie, C., Villalbí, J.R.
(2004). Socio-Economic
indexes in Surveys for Comparisons between Countries. Social Indicators Research 67, 315 - 332. [5] Boj, E., Claramunt,
M.M., Fortiana, J. (2007). Selection of predictors
in distance-based regression. Communications
in Statistics-Simulation and Computation 36 (1), 87–98. [6] Boj, E., Claramunt,
M.M., Grané, A., Fortiana, J. (2007). Implementing PLS for distance-based regression:
computational issues. Computational
Statistics 22 (2), 237–248. [7] Boj, E., Claramunt,
M.M., Grané, A., Fortiana, J. (2009). Projection Error Term in Gower's Interpolation. Journal of Statistical Planning and
Inference 139, 1867–1878. [8] Boj, E.,
Delicado, P., Fortiana, J. (2010). Distance-based local linear regression for
functional predictors. Computational
Statistics and Data Analysis 54, 429–437. [9] Buzon MJ, Erkizia
I, Pou C, Minuesa G, Puertas MC, Esteve A, Castello A, Santos JR, Prado JG, Izquierdo-Useros
N, Pattery T, Van Houtte
M, Carrasco L, Clotet B, Ruiz L, Martinez-Picado J.(2012) A non-infectious cell-based phenotypic
assay for the assessment of HIV-1 susceptibility to protease inhibitors. Journal of Antimicrobial
Chemotherapy 67(1):32-8. [10] Carnicer-Pont D, Almeda
J, Luis Marin J, Martinez
C, Gonzalez-Soler MV, Montoliu A, Muñoz R, Casabona J; HIV NADO working group (2011) Unlinked anonymous testing to estimate HIV prevalence among pregnant women in Catalonia, Spain, 1994
to 2009. Eurosurveillance, 16(32), pii:
19940. Erratum in: Eurosurveillance, 2011,16(33).pii/19945. [11] Esteve, A., Boj, E., Fortiana, J. (2009). Interaction Terms in
Distance-Based Regression. Communications
in Statistics Part A-Theory and Methods 38, 3499-3509. [12] Folch C, Casabona
J, Brugal MT, Majó X, Esteve A, Meroño
M, Gonzalez V; REDAN Study
Group (2011) Sexually transmitted
infections and sexual practices
among injecting drug users in harm reduction centers in Catalonia. European Addiction Research,17(5),
271-8, Epub 2011 Jul 27. [13] Fortiana, J., Grané, A. (2002). A scale-free goodness-of-fit statistic for the
exponential distribution based on maximum correlations, Journal of Statistical Planning and Inference 108, 85 – 97. [14] Fortiana, J., Grané, A. (2003). Goodness-of-fit tests based on maximum correlations
and their orthogonal decompositions. Journal
of the Royal Statistical Society Series B-Methodological 65, 115 -126. [15] Gómez,
E., Gómez-Villegas, M.A., Marín, J.M.
(2002). Continuous
elliptical and exponential power linear dynamic models. Journal of Multivariate
Analysis 83, 22 -36. [16] Gómez,
E., Gómez-Villegas, M.A., Marín, J.M.
(2002). A matrix variate generalization of the power exponential family of
distributions. Communications in Statistics-Theory
and Methods 31, 2167 -
2182. [17] Gómez,
E., Gómez-Villegas, M.A., Marín, J.M.
(2006). Sequences
of elliptical distributions and mixtures of normal distributions. Journal of Multivariate
Analysis 97, 295 -310. [18] Gómez,
E., Gómez-Villegas, M.A., Marín, J.M.
(2008). A
multivariate exponential power distribution as mixture of normal
distributions with Bayesian applications. Communications in Statistics-Theory
and Methods 37, 972 - 985. [19] Grané, A. (2012) Exact
goodness-of-fit tests for censored data. Annals
of the Institute of Statistical Mathematics 64, 1187-1203 (http://www.springerlink.com/content/y08660j60k875x86/) [20] Grané, A., Fortiana, J. (2006). An adaptive goodness-of-fit test. Communications in Statistics-Theory
and Methods 35, 1141-1155. [21] Grané, A., Fortiana, J. (2008). Karhunen-Loève basis in
goodness-of-fit tests decomposition: an evaluation. Communications in Statistics-Theory
and Methods 37, 3144-3163. [22] Grané, A., Fortiana, J. (2009). A location and scale-free goodness-of-fit statistic
for the exponential distribution based on maximum correlations. Statistics
43, 1-12. [23] Grané, A., Fortiana, J. (2011). A directional test of exponentiality
based on maximum correlations. Metrika 73, 255 - 274. [24] Grané, A., Tchirina,
A. (2013). Asymptotic properties of a goodness-of-fit test. To appear in Statistics, 44(1), 202-215 (http://www.tandfonline.com/doi/abs/10.1080/02331888.2011.588709) [25] Grané, A., Veiga, H. (2008). Accurate minimum capital risk requirements: A comparison of several
approaches. Journal of Banking and
Finance 32, 2482-2492. [26] Grané, A., Veiga, H. (2010). Wavelet-based detection of outliers in financial time series. Computational Statistics and
Data Analysis, 54, 2580 - 2593. [27] Grané, A., Veiga, H. (2012) Asymmetry, realised volatility and stock return risk estimates. Portuguese Economic Journal, 11, 147-164 (http://www.springerlink.com/content/bxt74455q88g1825/?MUD=MP) [28] Guitart, C., A. Hernández-del-Valle, J.M.
Marin and J. Benedicto (2012) Tracking Temporal
Trend Breaks of Anthropogenic Change in Mussel Watch (MW) Databases. Environmental Science & Technology,
46(21), 11515-11523. [29] HIV-CAUSAL Collaboration, Cain LE, Logan R, Robins JM, Sterne JA, Sabin C, Bansi L, Justice A, Goulet J, van Sighem A, de Wolf F, Bucher HC, von Wyl V, Esteve A, Casabona
J, del Amo J, Moreno S, Seng R, Meyer
L, Perez-Hoyos S, Muga R, Lodi
S, Lanoy E, Costagliola
D, Hernan MA.(2011) When to initiate combined antiretroviral therapy to reduce mortality and AIDS-defining illness in HIV-infected persons in developed countries:
an observational study. Annals of Internal
Medicine, 19, 154(8), 509-15. [30] Llibre JM, Buzón
MJ, Massanella M, Esteve A, Dahl V, Puertas MC, Domingo P, Gatell JM, Larrouse M,
Gutierrez M, Palmer S, Stevenson M, Blanco J, Martinez-Picado
J, Clotet B. (2011) Treatment intensification with raltegravir in subjects with sustained HIV-1 viremia suppression: a randomized 48 weeks study. Antiviral
Therapy (in press). [31] Marín, J.M.,
Montes, R., Ríos, D. (2003). Bayesian Methods in Plant Conservation Biology. Biological Conservation
113, 379- 387. [32] Marín, J.M.,
Plà, L.M., Ríos, D. (2004). Inference for some stochastic
process models related with sow management. Journal of Applied
Statistics 32, 797 - 812. [33] Marín, J.M. and Rodríguez-Bernal,
M.T. (2012). Multiple hypothesis testing and
clustering with mixtures of non-central t-distributions applied in microarray
data analysis. Computational Statistics
and Data Analysis. (http://www.sciencedirect.com/science/article/pii/S0167947311004130). [34] Marín, J.M.,
Rodríguez-Bernal, M.T., Wiper, M. (2005). Using Weibull
mixture distributions to model heterogeneous survival data. Communications in Statistics-Simulation
and Computation 34, 673
- 684. [35] Marín, J.M.,
Nieto, C. (2008). Spatial
matching of multiple configurations of points with Bioinformatics
application. Communications in Statistics-Theory
and Methods 37, 1977 -1995. [36] Pérez,
A. Ruiz, E., Veiga, H. (2009). A note on the properties of power-transformed
returns in long-memory stochastic volatility models with leverage effect. Computational Statistics and Data Analysis 53, 3593 - 3600. [37] Pedrosa E, Carretero-Iglesia L, Boada A, Colobran
R, Faner R, Pujol-Autonell
I, Palou E, Esteve A, Pujol-Borrell R, Ferrándiz C,
Juan M, Carrascosa JM. (2011) CCL4L polymorphisms
and CCL4/CCL4L serum levels
are associated with psoriasis severity. Journal
of Investigative Dermatology,
131(9), 1830-7, doi: 10.1038/jid.2011.127. [38] Pérez A, Giménez M, Sala P,
Sierra M, Esteve A, Rodrigo
C.(2011) Increase in invasive
nonvaccine pneumococcal serotypes at two hospitals in
Barcelona: was replacement
disease to blame?
Acta Paediatrica, 100(12):1572-5, doi:
10.1111/j.1651-2227.2011.02365.x [39] Ramos,
S. B. and Veiga,
H. (2011) Risk
factors in oil and gas industry returns: International evidence, Energy Economics, 33(3), 525-542 [40] Romero A, González V, Esteve A, Martró E, Matas L, Tural C, Pumarola T, Casanova
A, Ferrer E, Caballero E, Ribera E, Margall N,
Domingo P, Farré J, Puig T, Sauca
MG, Barrufet P, Amengual
MJ, Navarro G, Navarro M, Vilaró J, Ortín X, Amat Ortí15, Pujol F, Prats JM, Massabeu A, Simó JM, Villaverde
CA, Benítez MA, Garcia
I, Díaz O, Becerra J, Ros R, Sala R, Rodrigo I, Miró JM, Casabona J, and the AERI Study group. (2011) Identification of recent HIV-1
infection among newly diagnosed cases in Catalonia, Spain (2006-2008). European Journal
of Public Health (in press). [41] Ruiz, E., Veiga, H. (2008). Modelling long memory volatilities with leverage
effect: AlLMSV versus FIEGARCH. Computational Statistics and Data Analysis
52, 2846 - 2862. [42] Sánchez-Niubò, A., Fortiana, J.,
Barrio, G., Suelves, J.M., Correa, J.F., Domingo-Salvany, A. (2009). Problematic
heroin use incidence trends in Spain. Addiction 104,
248 - 255. [43] Vives, N., Carnicer-Pont,
D., García de Olalla, P., Camps, N., Esteve, A., Casabona,
J. and
the HIV and STI Surveillance Group. (2011) Factors associated to late
diagnosis of HIV infection in Catalonia, Spain. International Journal of STD & AIDS (In press). [44] Wiper,
M.P., Palacios, A.P. and Marín, J.M.
(2012). Bayesian software reliability prediction using software metrics information.
Quality Technology
and Quantitative Management 9, 1, p. 35-44. |
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