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A link function approach to heterogeneous variance components [PDF]

open access: bronzeGenetics Selection Evolution, 1998
This paper presents techniques of parameter estimation in heteroskedastic mixed models having i) heterogeneous log residual variances which are described by a linear model of explanatory covariates and ii) log residual and log u-components linearly related. This makes the intraclass correlation a monotonic function of the residual variance.
Jean‐Louis Foulley   +2 more
doaj   +9 more sources

On the Notion of Reproducibility and Its Full Implementation to Natural Exponential Families

open access: yesMathematics, 2021
Let F=Fθ:θ∈Θ⊂R be a family of probability distributions indexed by a parameter θ and let X1,⋯,Xn be i.i.d. r.v.’s with L(X1)=Fθ∈F. Then, F is said to be reproducible if for all θ∈Θ and n∈N, there exists a sequence (αn)n≥1 and a mapping gn:Θ→Θ,θ⟼gn(θ ...
Shaul K. Bar-Lev
doaj   +1 more source

Interval Kepercayaan Untuk Fungsi Nilai Harapan dan Fungsi Ragam Proses Poisson Periodik Majemuk

open access: yesJambura Journal of Mathematics, 2022
Compound cyclic Poisson process have the mean and variance functions. The objective of this paper is to construct confidence intervals for respectively the mean and variance functions of a compound cyclic Poisson process with significance level 0alpha1 ...
Auliya Fithry   +2 more
doaj   +1 more source

The Large Arcsine Exponential Dispersion Model—Properties and Applications to Count Data and Insurance Risk

open access: yesMathematics, 2022
The large arcsine exponential dispersion model (LAEDM) is a class of three-parameter distributions on the non-negative integers. These distributions show the specific characteristics of being leptokurtic, zero-inflated, overdispersed, and skewed to the ...
Shaul K. Bar-Lev, Ad Ridder
doaj   +1 more source

Optimization of Samples for Remote Sensing Estimation of Forest Aboveground Biomass at the Regional Scale

open access: yesRemote Sensing, 2022
Accurately estimating forest aboveground biomass (AGB) based on remote sensing (RS) images at the regional level is challenging due to the uncertainty of the modeling sample size.
Qingtai Shu   +5 more
doaj   +1 more source

Confidence Interval for Variance Function of a Compound Periodic Poisson Process with a Power Function Trend

open access: yesJTAM (Jurnal Teori dan Aplikasi Matematika), 2023
This research is a follow-up research of Utama (2022) on asymptotic distribution of an estimator for variance function of a compound periodic Poisson with the power function trend.
Ade Irawan   +2 more
doaj   +1 more source

Discrimination between Some Over Dispersed Count Distributions

open access: yesASM Science Journal, 2021
The Poisson inverse Gaussian and generalized Poisson distributions are widely used in modelling overdispersed count data which are commonly found in healthcare, insurance, engineering, econometric and ecology.
Yook-Ngor Phang   +2 more
doaj   +1 more source

New Closed Form Estimators for the Beta Distribution

open access: yesMathematics, 2023
In this paper, we detail closed form estimators for beta distribution that are simpler than those proposed by Tamae, Irie and Kubokawa. The proposed estimators are shown to have smaller asymptotic variances and smaller asymptotic covariances compared to ...
Victor Mooto Nawa, Saralees Nadarajah
doaj   +1 more source

Jackknife Empirical Likelihood Inference for the Variance Residual Life Function

open access: yesRevstat Statistical Journal, 2021
In life testing situations, the residual life time of a component which has survived t units of time is Xt = X −t|X > t. In this paper, we give a central limit theorem result for the estimator of Var(Xt), the variance residual life(VRL) function.
Vali Zardasht
doaj   +1 more source

Wavelet estimations of the derivatives of variance function in heteroscedastic model

open access: yesAIMS Mathematics, 2023
This paper studies nonparametric estimations of the derivatives $ r^{(m)}(x) $ of the variance function in a heteroscedastic model. Using a wavelet method, a linear estimator and an adaptive nonlinear estimator are constructed.
Junke Kou, Hao Zhang
doaj   +1 more source

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