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Statistical inference from set-valued observations
Statistical inference set-valued observations
2009/9/22
Consider a random experiment whose true (unknown)
outcome is modelled by a certain random element X and the available
imprecise observations are modelled by some random set A such that
XE A almost ...
Bivariate Ordinal Data in the Perspective of the Wisconsin Epidemiologic Study of Diabetic Retinopathy: Different Statistical Directions
Bivariate Ordinal Data Diabetic Retinopathy Different Statistical Directions
2009/9/17
Bivariate Ordinal Data in the Perspective of the Wisconsin Epidemiologic Study of Diabetic Retinopathy: Different Statistical Directions。
Statistical Analysis for Longitudinal Counting Data in the Presence of a Covariate Considering Different
Statistical Analysis Longitudinal Counting Data
2009/9/17
Statistical Analysis for Longitudinal Counting Data in the Presence of a Covariate Considering Different "Frailty" Models。
The false discovery rate for statistical pattern recognition
Statistical learning theory generalization error false discovery rate
2009/9/16
The false discovery rate (FDR) and false nondiscovery rate (FNDR) have received considerable attention in the literature on multiple testing. These performance measures are also appropriate for classi...
Statistical minimax approach of the Hausdorff moment problem
Minimax estimation Statistical inverse problems Problemof the moments Legendre polynomials Kullback-Leibler information
2010/4/29
The purpose of this paper is to study the problem of estimating a compactly
supported function from noisy observations of its moments in an ill-posed
inverse problem framework. We provide a statisti...
Statistical methods for cosmological parameter selection and estimation
Statistical methods cosmological parameter selection estimation
2010/3/19
The estimation of cosmological parameters from precision observables is an important indus-
try with crucial ramifications for particle physics. This article discusses the statistical methods
presen...
SMART：A statistical framework for optimal design matrix generation with application to fMRI
statistical framework optimal design matrix generation fMRI
2010/3/18
The general linear model (GLM) is a well established tool for analyzing functional magnetic resonance imaging (fMRI) data. Most fMRI analyses via GLM proceed in a massively univariate
fashion where t...
Contributions of Professor Hirotugu Akaike in Statistical Science
ABIC AIC Bayes modeling FPE frequency domain analysis time series analysis time series models TIMSAC
2009/3/5
Prof. Akaike made significant contributions in various fields of statistical science, in particular, in time series analysis in frequency domain and time domain, information criterion and Bayes modeli...
Inference on a Set of Statistical Models
AIC CIC confidence set of models generalized likelihood ratio test GIC information criteria
2009/3/5
The paper outlines some aspects related to statistical model selection, focusing in particular on inference conducted in the presence of a finite set of parametric models. The point the paper emphasiz...
Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates
Ancillary variables de-noise linear model errors-in-variable profile least-square-based estimator rational expection model
2010/3/18
We study semiparametric varying-coefficient partially linear models
when some linear covariates are not observed, but ancillary variables
are available. Semiparametric profile least-square based est...
AsympTest: an R package for performing parametric statistical tests and confidence intervals based on the central limit theorem
parametric tests and confidence intervals central limit theorem R package
2010/3/18
This paper describes an R package implementing large sample tests and confidence
intervals (based on the central limit theorem) for various parameters. The one and
two sample mean and variance conte...
STATISTICAL EVALUATION OF METHODS FOR THE ANALYSIS OF DYNAMIC PROTEIN EXPRESSION DATA FROM A TUMOR STUDY
protein expression data proteome data preprocessing missing values imputation longitudinal data analysis neuroblastoma
2009/2/25
In this article, we analyze time dependent protein expression data obtained from
a proteome study of a neuroblastoma cell line. Neuroblastoma are common solid
tumors which occur in early childhood. ...
QUALITY CONTROL AND LOW-LEVEL STATISTICAL ANALYSIS OF ILLUMINA BEADARRAYS
Illumina BeadArray beadarray Bioconductor microarray
2009/2/25
The Illumina BeadArrayTM platform is a novel microarray technology based on ran-
domly assembled arrays of beads. Each bead on the array carries copies of a single
gene-specific probe with, on avera...
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes
event sequences spike trains multi-electrode array microcircuits temporal data mining frequentepisodes
2010/3/18
Identifying the spatio-temporal network structure of brain activity from multi-neuronal data streams is one of the biggest challenges in neuroscience. Repeating patterns of precisely timed activity ac...
About one problem of Bernoulli and Euler from the theory of statistical estimation
Asymptotic normality sample mean Bernoulli’s estimator Euler’s estimator maximum likelihood unbiased estimator
2009/2/23
We consider some results by D. Bernoulli and L. Euler on the method of maximum likelihood in
parametric estimation. The statistical analysis is made by considering a parametric family with a shift pa...