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Journal of Statistical Software
Scopus
ISSN 1548-7660 · Foundation for Open Access Statistics · 1.692 artikel di indeks
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Artikel Jurnal
pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
Bayesian nonparametric models have proven to be successful tools for clustering and density estimation. While there exists a nourished ecosystem of implementations in R, for Python there are only a few. Here we develop a Python package called pyrichlet, for Bayesian nonparametric density estimation…
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Artikel Jurnal
BayesMix: Bayesian Mixture Models in C++
We describe BayesMix, a C++ library for MCMC posterior simulation for general Bayesian mixture models. The goal of BayesMix is to provide a self-contained ecosystem to perform inference for mixture models to computer scientists, statisticians and practitioners. The key idea of this library is…
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Stability Selection and Consensus Clustering in R: The R Package sharp
The R package sharp (Stability-enHanced Approaches using Resampling Procedures) provides an integrated framework for stability-enhanced variable selection, graphical modeling and clustering. In stability selection, a feature selection algorithm is combined with a resampling technique to estimate…
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Parsimoniously Fitting Large Multivariate Random Effects in glmmTMB
Multivariate random effects with unstructured variance-covariance matrices of large dimensions, q, can be a major challenge to estimate. In this paper, we introduce a new implementation of a reduced-rank approach to fit large dimensional multivariate random effects by writing them as a linear…
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Artikel Jurnal
Split-Apply-Combine with Dynamic Grouping
Partitioning a data set by one or more of its attributes and computing an aggregate for each part is one of the most common operations in data analyses. There are use cases where the partitioning is determined dynamically by collapsing smaller subsets into larger ones, to ensure sufficient support…
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Artikel Jurnal
RESI: An R Package for Robust Effect Sizes
Effect size indices are useful parameters that quantify the strength of association and are unaffected by sample size. There are many available effect size parameters and estimators, but it is difficult to compare effect sizes across studies as most are defined for a specific type of population…
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Artikel Jurnal
TrueSkill Through Time: Reliable Initial Skill Estimates and Historical Comparability with Julia, Python, and R
Knowing how individual abilities change is essential in a wide range of activities. The most widely used skill estimators in industry and academia (such as Elo and TrueSkill) propagate information in only one direction, from the past to the future, preventing them from obtaining reliable initial…
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Artikel Jurnal
Learning Permutation Symmetry of a Gaussian Vector with gips in R
The study of hidden structures in data presents challenges in modern statistics and machine learning. We introduce the gips package in R, which identifies permutation subgroup symmetries in Gaussian vectors. gips serves two main purposes: Exploratory analysis in discovering hidden permutation…
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Artikel Jurnal
gptools: Scalable Gaussian Process Inference with Stan
Gaussian processes (GPs) are sophisticated distributions to model functional data. Whilst theoretically appealing, they are computationally cumbersome except for small datasets. We implement two methods for scaling GP inference in Stan: First, a general sparse approximation using a directed acyclic…
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hibayes: An R Package to Fit Individual-Level, Summary-Level and Single-Step Bayesian Regression Models for Genomic Prediction and Genome-Wide Association Studies
With the rapid development of sequencing technology, the costs of individual genotyping have been reduced dramatically, leading to genomic prediction and genome-wide association studies being widely promoted and used to predict the unknown phenotypes and to locate candidate genes for animal and…
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Mixed-Effects Additive Transformation Models with the R Package tramME
Regression models that accommodate correlated observations and potential nonlinear predictor-outcome relationships are fundamental in analyzing experimental and observational data. Unlike traditional parametric approaches, transformation models make weaker assumptions on the conditional response…
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Artikel Jurnal
pymle: A Python Package for Maximum Likelihood Estimation and Simulation of Stochastic Differential Equations
This paper introduces the object-oriented Python package pymle, which provides core functionality for maximum likelihood estimation and simulation of univariate stochastic differential equations. The package supports maximum likelihood estimation using Euler, Elerian, Ozaki, Shoji-Ozaki, Hermite…
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NUBO: A Transparent Python Package for Bayesian Optimization
NUBO, short for Newcastle University Bayesian Optimisation, is a Bayesian optimization framework for the optimization of expensive-to-evaluate black-box functions, such as physical experiments and computer simulators. Bayesian optimization is a costefficient optimization strategy that uses…
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hmmTMB: Hidden Markov Models with Flexible Covariate Effects in R
Hidden Markov models (HMMs) are widely applied in studies where a discrete-valued process of interest is observed indirectly. They have for example been used to model behavior from human and animal tracking data, disease status from medical data, and financial market volatility from stock prices…
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TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in R
TSCI implements treatment effect estimation from observational data under invalid instruments in the R statistical computing environment. Existing instrumental variable approaches rely on arguably strong and untestable identification assumptions, which limits their practical application. TSCI does…
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Quantile Regression under Limited Dependent Variable in Stata
This article develops a Stata command, ldvqreg, to estimate quantile regression models for the cases of censored (with lower and/or upper censoring) and binary dependent variables. The estimator is implemented using a smoothed version of the quantile regression objective function. Simulation…
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Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall
The R package optimall offers a collection of functions that efficiently streamline the design process of sampling in surveys ranging from simple to complex. The package's main functions allow users to interactively define and adjust strata cut points based on values or quantiles of auxiliary…
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singleRcapture: An R Package for Single-Source Capture-Recapture Models
Population size estimation is a major challenge in official statistics, social sciences, and natural sciences. The problem can be tackled by applying capture-recapture methods, which vary depending on the number of sources used, particularly on whether a single or multiple sources are involved…
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Artikel Jurnal
Exploring Data Subsets with vtree
Variable trees are a new method for the exploration of discrete multivariate data. They display nested subsets and corresponding frequencies and percentages. Manual calculation of these quantities can be laborious, especially when there are many multi-level factors and missing data. Here we…
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Artikel Jurnal
equateMultiple: An R Package to Equate Multiple Forms
Item response theory (IRT) provides a framework for modeling the responses given to a test or questionnaire, which are assumed to depend on an underlying latent variable and on some item parameters. Due to identifiability issues, when the parameters are estimated separately on different datasets…
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