- Referenced in 172 articles
- contour plots. Fitting copula models including variance estimates. Independence and serial (univariate and multivariate) independence...
- Referenced in 119 articles
- nonlinear regression model and generalized least squares estimates for a multivariate nonlinear regression model ... options can be set to correct variance estimates for heteroskedasticity and/or serial correlation. For simultaneous...
- Referenced in 63 articles
- expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated ... expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions...
- Referenced in 60 articles
- based on the negative binomial distribution. Estimate variance-mean dependence in count data from high...
- Referenced in 22 articles
- address the ”missing heritability” problem. GCTA estimates the variance explained by all the SNPs ... GCTA’s five main functions: data management, estimation of the genetic relationships from SNPs, mixed ... linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure ... focus on the function of estimating the variance explained by all the SNPs...
- Referenced in 27 articles
- based on the negative binomial distribution. Estimate variance-mean dependence in count data from high ... Huber W, Anders S (2014). “Moderated estimation of fold change and dispersion...
- Referenced in 14 articles
- Hierarchical empirical Bayes model shrinks variance estimates and increases sensitivity of the analysis. It allows...
- Referenced in 30 articles
- order model of the variances and covariances of evolutionary distance estimates. This model is well ... adapted when these estimates are obtained from aligned sequences. At each step it permits ... variance of the new distance matrix. In this way, we obtain better estimates to choose...
- Referenced in 11 articles
- covariance estimation by the nearest neighbor variance estimation (NNVE) method of Wang and Raftery...
- Referenced in 26 articles
- individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring ... factor of the random-effects variance-covariance matrix is estimated, along with the effects...
- Referenced in 17 articles
- Fisz’ technique for estimating the time-varying, piecewise constant local variance of a locally stationary ... series. We apply our technique to the estimation of the spectral structure in the locally ... Haar wavelets and the variance stabilizing Fisz transform. The resulting estimator is mean square consistent ... Fisz transform’, a device for stabilizing the variance of scaled $chi^2$-data and bringing...
- Referenced in 35 articles
- Modelling , Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance decomposition and impulse...
- Referenced in 24 articles
- type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations ... package also provides shrinkage estimators for partial correlations and partial variances. The inverse...
- Referenced in 5 articles
- sample structure, and for estimating the proportion of variance in phenotypes explained (PVE) by typed ... while controlling for population structure. It estimates variance component/chip heritability, and partitions it by different ... regression or REML AI algorithm to estimate variance components when individual-level data are available ... uses MQS to estimate variance components when only summary statisics are available...
- Referenced in 20 articles
- priors imply about the total proportion of variance in outcome explained by relevant covariates ... potential for BVSR to estimate this proportion of variance explained, and hence shed light...
- Referenced in 52 articles
- maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor...
- Referenced in 11 articles
- derived from the loglinear parameter estimates; their variances are obtained by linearization. The novel feature...
- Referenced in 19 articles
- experiments. The voom method estimates the mean-variance relationship of the log-counts, generates...
- Referenced in 33 articles
- false discoveries variance in multiple tests. The model parameters are estimated thanks...
- Referenced in 4 articles
- WesVar. Replication-Based Variance Estimation for Analysis of Complex Survey Data. WesVar® uses the robust ... flexible approach of replication variance estimation. Replication methods apply to sample designs and estimators from...