Results 81 to 90 of about 219,896 (196)

COENOTIC DISTRIBUTION AND ECOLOGICAL PREFERENCES OF SPHAGNA IN NOTHERN TAIGA, EUROPEAN RUSSIA (PINEZHSKY STRICT NATURE RESERVE, ARKHANGELSK REGION)

open access: yesTransactions of the Karelian Research Centre of the Russian Academy of Sciences, 2017
Here we consider the coenotic distribution of 23 species of the genus Sphagnum and their relation to prime ecological factors in Pinezhsky Strict Nature Reserve (Arkhangelsk Region, north of European Russia).
Sergei Popov, Vladimir Fedosov
doaj   +1 more source

Missing covariates in logistic regression, estimation and distribution selection. [PDF]

open access: yes
We derive explicit formulae for estimation in logistic regression models where some of the covariates are missing. Our approach allows for modeling the distribution of the missing covariates either as a multivariate normal or multivariate t-distribution.
Claeskens, Gerda, Consentino, Fabrizio
core  

Model Comparison of Coordinate-Free Multivariate Skewed Distributions with an Application to Stochastic Frontiers [PDF]

open access: yes
We consider classes of multivariate distributions which can model skewness and are closed under orthogonal transformations. We review two classes of such distributions proposed in the literature and focus our attention on a particular, yet quite flexible,
Jose T.A.S. Ferreira, Mark F.J. Steel
core  

Limited and full information estimation and goodness-of-fit testing in 2n contingency tables [PDF]

open access: yes
(WP 14/03 Clave pdf)High-dimensional contingency tables tend to be sparse and standard goodness-of-fit statistics such as X 2 cannot be used without pooling categories.As an improvement on arbitrary pooling, for goodness-of-fit of large 2 n contingency ...
ALBERTO MAYDEU
core  

On Estimated Projection Pursuit-Type Cramer-von Mises Statistics

open access: yes, 1997
This paper addresses the problem of testing for a multivariate distribution, which belongs to a known parametric distribution family. The estimated Cramer-Von Mises-type test statistics are constructed using projection pursuit technique.
Bhatti, Ishaq   +2 more
core   +1 more source

A note on testing for homoscedasticity in high-dimensional time series

open access: yesResearch in Statistics
We consider the problem of testing for homoscedasticity in high-dimensional time series, under the assumption that the sample size n and the dimension p satisfy [Formula: see text] as [Formula: see text]. The homoscedasticity refers to the case where the
Yosei Yoshida, Yan Liu
doaj   +1 more source

Asymptotic distributions of a test statistic in multivariate linear relationships

open access: yesJournal of the Japan Statistical Society, Japanese Issue, 1992
Summary: For testing problems of the coefficient vectors of \(p\)-variate linear functionals and structured relationships, a statistic which is based on the multiple correlation coefficient between the null variate and the uncorrelated \((p-1)\) variates is considered.
openaire   +2 more sources

Depth functions based on a number of observations of a random vector [PDF]

open access: yes, 2007
We present two statistical depth functions given in terms of the random variable defined as the minimum number of observations of a random vector that are needed to include a fixed given point in their convex hull.
Cascos Fernández, Ignacio   +1 more
core  

Stratification of cephalosporins based on physicochemical and pharmacokinetic variables using multivariate statistical tools

open access: yesIntelligent Pharmacy
Introduction: Cephalosporins, a class of beta-lactam antibiotics, are commonly used in medical practice. However, their potential advantages, based on physicochemical and pharmacokinetic variables, are often overlooked.
Carlos Alberto Escobar Angulo   +2 more
doaj   +1 more source

Multivariate Pareto distribution [PDF]

open access: yes, 2019
Title: Multivariate Pareto distribution Author: Oleksandr Novytskyi Department: Department of Probability and Mathematical Statistics (305. 32- KPMS) Supervisor: RNDr. Lucie Mazurová, Ph.D., Department of Probability and Mathematical Statistics (305.
Novytskyi, Oleksandr
core  

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