Results 151 to 160 of about 10,792 (301)

A Tutorial on Conducting and Interpreting a Bayesian Independent T‐Test Using Open‐Source Software

open access: yesJournal of Advanced Nursing, EarlyView.
ABSTRACT Aim To demonstrate a worked‐out example of a Bayesian independent t‐test using open‐source software, simulated data, a hypothetical nurse education intervention and a randomised controlled study design. This tutorial explains relevant Bayesian concepts and highlights literature that provides statistically principled justifications for ...
Helen Evelyn Malone, Imelda Coyne
wiley   +1 more source

Dream habits in a large cohort of preteens and their relation to sleep and nocturnal awakenings

open access: yesJournal of Sleep Research, Volume 34, Issue 2, April 2025.
Summary The present study examined dream habits, and their relation to sleep patterns, in 1151 preteens (597 boys; 554 girls; 11.31 ± 0.62 years old). Dream questionnaires assessed the frequency of dream recall, nightmare, and lucid dream, as well as the intensity of emotions experienced in dreams. Sleep variables included sleep duration and efficiency,
Jean‐Baptiste Eichenlaub   +3 more
wiley   +1 more source

Non-subjective priors for wrapped Cauchy distributions

open access: green, 2019
Malay Ghosh   +3 more
openalex   +2 more sources

Change Point Analysis for Functional Data Using Empirical Characteristic Functionals

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We develop a new method to detect change points in the distribution of functional data based on integrated CUSUM processes of empirical characteristic functionals. Asymptotic results are presented under conditions allowing for low‐order moments and serial dependence in the data establishing the limiting null‐distribution of the proposed test ...
Lajos Horváth   +2 more
wiley   +1 more source

Tensor Changepoint Detection and Eigenbootstrap

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT Tensor data consisting of multivariate outcomes over the items and across the subjects with longitudinal and cross‐sectional dependence are considered. A completely distribution‐free and tweaking‐parameter‐free detection procedure for changepoints at different locations is designed, which does not require training data.
Michal Pešta   +2 more
wiley   +1 more source

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