Search
Search Results
-
Extrinsic Regression and Anti-Regression on Projective Shape Manifolds
Necessary and sufficient conditions for the existence of the extrinsic mean and extrinsic antimean of a random object (r.o.) X on a compact metric...
-
ECM Algorithm for Auto-Regressive Multivariate Skewed Variance Gamma Model with Unbounded Density
The multivariate skewed variance gamma (MSVG) distribution is useful in modelling data with high density around the location parameter along with...
-
Gaussian Asymptotic Limits for the α-transformation in the Analysis of Compositional Data
Compositional data consists of vectors of proportions whose components sum to 1. Such vectors lie in the standard simplex, which is a manifold with...
-
Robust quantile estimation under bivariate extreme value models
In risk quantification of extreme events in multiple dimensions, a correct specification of the dependence structure among variables is difficult due...
-
On a General Class of Discrete Bivariate Distributions
In this paper we develop a general class of bivariate discrete distributions. The basic idea is quite simple. The marginals are obtained by taking...
-
Some Point Estimates and Confidence Regions for Multivariate Inter-laboratory Data Analysis
The problem of analyzing multivariate data from inter-laboratory studies is considered when the data are modeled using the heteroscedastic...
-
Multiple Categorical Covariates-Based Multinomial Dynamic Response Model
Regression models for multinomial responses with time dependent covariates have been studied recently both in longitudinal and time series setup. For...
-
Recent developments in high dimensional covariance estimation and its related issues, a review
In this paper we review some of recent developments in high dimensional data analysis, especially in the estimation of covariance and precision...
-
High-dimensional grouped folded concave penalized estimation via the LLA algorithm
The group folded concave penalization problems have been shown to process the satisfactory oracle property theoretically. However, it remains unknown...
-
Compressed Covariance Estimation with Automated Dimension Learning
We propose a method for estimating a covariance matrix that can be represented as a sum of a low-rank matrix and a diagonal matrix. The proposed...
-
A New Look at the Models for Ordinal Categorical Data Analysis
The multinomial/categorical responses, whether they are nominal or ordinal, are recorded in counts under all categories/cells involved. The analysis...
-
Hierarchically penalized quantile regression with multiple responses
We study variable selection in quantile regression with multiple responses. Instead of applying conventional penalized quantile regression to each...
-
Dynamic Non-parametric Monitoring of Air-Pollution
Air pollution poses a major problem in modern cities, as it has a significant effect in poor quality of life of the general population. Many recent...
-
A Test for Multivariate Location Parameter in Elliptical Model Based on Forward Search Method
In this article, we develop a test for multivariate location parameter in elliptical model based on the forward search estimator for a specified...
-
A bivariate distribution with Lomax and geometric margins
We develop a stochastic model describing the joint distribution of (X, N), where N has a geometric distribution while X is the sum of N dependent,...
-
Inference in the Growth Curve Model under Multivariate Skew Normal Distribution
Existing methods for estimating the parameters of the Growth Curve Model (GCM) rely on the assumption that the underlying distribution for the error...
-
Multiscale representation for irregularly spaced data
In this paper, we propose a multiscale method for representing inhomogeneous functions (surfaces) from irregularly spaced noisy observations that...
-
Inferences in Binary Dynamic Fixed Models in a Semi-parametric Setup
In a longitudinal setup, the so-called generalized estimating equations approach was a popular inference technique to obtain efficient regression...
-
Law of large numbers for discretely observed random functions
A strong law of large numbers for continuous random functions, and associated tensor product surfaces is established in the setup of discretely...
-
A Parameter Dimension-Split Based Asymptotic Regression Estimation Theory for a Multinomial Panel Data Model
In this paper we revisit the so-called non-stationary regression models for repeated categorical/multinomial data collected from a large number of...