Results 21 to 30 of about 46,298 (299)

Testing the martingale difference hypothesis using integrated regression functions [PDF]

open access: yes, 2006
An omnibus test for testing a generalized version of the martingale difference hypothesis (MDH) is proposed. This generalized hypothesis includes the usual MDH, testing for conditional moments constancy such as conditional homoscedasticity (ARCH effects)
Velasco Gómez, Carlos   +6 more
core   +1 more source

A Testing for New Renewal Better than Used Class of Survival Functions [PDF]

open access: yesThe Egyptian Statistical Journal, 2000
A U-statistic is derived for testing exponentiality against new renewal better (worse) than used. For this class of life distributions, a nonparametric procedure (U-statistic) is presented in this investigation. Selected critical values are tabulated for
M. Hendi
doaj   +1 more source

Bootstrap Statistical Inference for the Variance Based on Fuzzy Data

open access: yesAustrian Journal of Statistics, 2016
The bootstrap is a simple and straightforward method for calculating approximated biases, standard deviations, confidence intervals, testing statistical hypotheses, and so forth, in almost any nonparametric estimation problem. In this paper we describe a
Mohammad Ghasem Akbari   +1 more
doaj   +1 more source

Testing jumps via false discovery rate control. [PDF]

open access: yesPLoS ONE, 2013
Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such ...
Yu-Min Yen
doaj   +1 more source

A technique for testing hypotheses for distributions of multidimensional spectral data using a nonparametric pattern recognition algorithm [PDF]

open access: yesКомпьютерная оптика, 2019
The paper deals with a new method of testing hypotheses for the distribution of multidimensional remote sensing spectral data. The proposed technique is based on the use of nonparametric algorithms for pattern recognition.
Alexander Lapko, Vasily Lapko
doaj   +1 more source

Some hypothesis testing problems for categorical variables

open access: yesStatistica, 2007
This paper considers some testing problems for multivariate categorical variables within a conditional, or permutation, framework. The key idea is based on the decomposition of null and alternative hypotheses into a number of sub-hypotheses. For each sub-
Fortunato Pesarin
doaj   +1 more source

Nonparametric Bayes classification and hypothesis testing on manifolds

open access: yesJournal of Multivariate Analysis, 2012
Our first focus is prediction of a categorical response variable using features that lie on a general manifold. For example, the manifold may correspond to the surface of a hypersphere. We propose a general kernel mixture model for the joint distribution of the response and predictors, with the kernel expressed in product form and dependence induced ...
Abhishek Bhattacharya, David B. Dunson
openaire   +2 more sources

The application of modified free inquiry for the science process skills

open access: yesJurnal Mangifera Edu, 2022
This study aimed to improve students' science process skills by applying modified free inquiry, which is a modification of two approaches: guided inquiry and free inquiry. The research method used is true-experimental design.
Yeni Suryaningsih   +1 more
doaj   +1 more source

Analysis of Nonparametric and Parametric Criteria for Statistical Hypotheses Testing. Chapter 1. Agreement Criteria of Pearson and Kolmogorov

open access: yesСтатистика України, 2018
In the statistical analysis of experimental results it is extremely important to know the distribution laws of the general population. ‎Because of all assumptions about the distribution laws are statistical hypotheses, they should be tested.
F. V. Motsnyi
doaj   +1 more source

Innovation-Based Research Using Structural Flexibility and Acceptance Model (SFAM)

open access: yesCogent Business & Management, 2023
The research objectives are as follows: (1) Develop a solid structural model assuming normality and homoscedasticity. (2) Obtain the property estimator of the flexible and robust SFAM structural model.
  Solimun   +1 more
doaj   +1 more source

Home - About - Disclaimer - Privacy