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Jackknife Empirical Likelihood for Parametric Copulas
Copulas Empirical likelihood Interval estimation Jackknife
2016/1/19
For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi and Rivest (1995). Although interval esti...
Identifiability of causal effects for binary variables with data missing due to death
Causal inference Missing due to death Identifiability EM algorithm Bounds
2016/1/19
Summary: We discuss evaluation of causal effects with missing data due to death. Frangakis et al. (2007)proposed an approach for estimating the causal effects of interest under some assumptions. In th...
SBA-term: Sparse Bilingual Association for Terms
SBA-term Sparse Bilingual Association Terms
2016/1/19
Bilingual semantic term association is very use-ful in cross-language information retrieval, statistical machine translation, and many other applications in natural language processing. In this paper,...
A Residual Based Multiple Testing Procedure for Variance Changepoints
Multiple testing Admissibility Multiple change points Variance change
2016/1/19
In this paper, we approach the variance changepoints detection problem from a multiple testing setting. After proving that the standard Step-Up and Step-Down procedures are inadmissible for the standa...
Qualitative implication and equivalence relations between treatment effects on surrogates and endpoints
Causal effect Prentice’s criterion Surrogate endpoint
2016/1/19
By the criterion for surrogates proposed by Prentice (1989), a null treatment effect on a surrogate implies a null treatment effect on a true endpoint.In this paper, we show that there may exist simul...
Support Vector Machines,Kernel Logistic Regression,and Boosting
Support Vector Machines Kernel Logistic Regression Boosting
2015/8/21
Support Vector Machines,Kernel Logistic Regression,and Boosting.
Classification of Gene Microarrays by P enalized Logisti Regression
cancer diagnosis feature selection logistic regression microarray support vector machines
2015/8/21
Classification of Gene Microarrays by P enalized Logisti Regression.
Assessing the significance of global and local correlations under spatial autocorrelation;a nonparametric approach
Geostatistics Monte-Carlo methods Resampling Spatial autocorrelation Spatial statistics Variogram
2015/8/21
In this paper we present a method to assess the significance of the correlation coefficient when at least one of the variables is spatially autocorrelated. The standard test assumes independence of th...
For high dimensional supervised learning problems, often using problem specific assumptions can lead to greater accuracy. For problems with grouped covariates, which are believed to have sparse effect...
Inference from presence-only data;the ongoing controversy
presence-only data ongoing controversy
2015/8/21
Presence-only data abounds in ecology, often accompanied by a background sample. Although many interesting aspects of the species’ distribution can be learned from such data, one cannot learn the over...
Learning interactions via hierarchical group-lasso regularization
hierarchical interaction computer intensive regression logistic
2015/8/21
We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be non...
A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression
Blockwise Descent Algorithm Group-penalized Multiresponse Multinomial Regression
2015/8/21
In this paper we purpose a blockwise descent algorithm for grouppenalized multiresponse regression. Using a quasi-newton framework we extend this to group-penalized multinomial regression. We give a p...
Learning the Structure of Mixed Graphical Models
Learning the Structure Mixed Graphical Models
2015/8/21
We consider the problem of learning the structure of a pairwise graphical model over continuous and discrete variables. We present a new pairwise model for graphical models with both continuous and di...
CATS regression–a model-based approach to studying trait-based community assembly
community composition community-level models fourth corner model generalised linear models maximum entropy Poisson regression
2015/8/21
CATS regression–a model-based approach to studying trait-based community assembly.
Confidence Intervals for Random Forests:The Jackknife and the Infinitesimal Jackknife
bagging jackknife methods Monte Carlo noise variance estimation
2015/8/21
We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging propos...