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The Journal of Statistical Software publishes articles on statistical software along with the source code of the software itself and replication code for all empirical results.
Site URL: www.jstatsoft.org
Feed URL: www.jstatsoft.org/index.php/jss/gateway/plugin/WebFeedGatewayPlugin/rss2
Posts: 12
Followers: 2
Weighted scoringRules: Emphasizing Particular Outcomes When Evaluating Probabilistic Forecasts
https://www.jstatsoft.org/index.php/jss/article/view/v110i08
Published: September 7, 2024 00:00
When predicting future events, it is common to issue forecasts that are probabilistic, in the form of probability distributions over the range of possible outcomes. Such forecasts can be evaluated using proper scoring rules. Proper scoring rules condense…
fairadapt: Causal Reasoning for Fair Data Preprocessing
https://www.jstatsoft.org/index.php/jss/article/view/v110i04
Published: September 7, 2024 00:00
Machine learning algorithms are useful for various prediction tasks, but they can also learn how to discriminate, based on gender, race or other sensitive attributes. This realization gave rise to the field of fair machine learning, which aims to…
cubble: An R Package for Organizing and Wrangling Multivariate Spatio-Temporal Data
https://www.jstatsoft.org/index.php/jss/article/view/v110i07
Published: August 29, 2024 00:00
Multivariate spatio-temporal data refers to multiple measurements taken across space and time. For many analyses, spatial and time components can be separately studied: for example, to explore the temporal trend of one variable for a single spatial…
An Extendable Python Implementation of Robust Optimization Monte Carlo
https://www.jstatsoft.org/index.php/jss/article/view/v110i02
Published: August 29, 2024 00:00
Performing inference in statistical models with an intractable likelihood is challenging, therefore, most likelihood-free inference (LFI) methods encounter accuracy and efficiency limitations. In this paper, we present the implementation of the LFI method…
anomaly: Detection of Anomalous Structure in Time Series Data
https://www.jstatsoft.org/index.php/jss/article/view/v110i01
Published: August 29, 2024 00:00
One of the contemporary challenges in anomaly detection is the ability to detect, and differentiate between, both point and collective anomalies within a data sequence or time series. The anomaly package has been developed to provide users with a choice of…
bayesnec: An R Package for Concentration-Response Modeling and Estimation of Toxicity Metrics
https://www.jstatsoft.org/index.php/jss/article/view/v110i05
Published: August 29, 2024 00:00
The bayesnec package has been developed for R to fit concentration (dose)-response curves (CR) to toxicity data for the purpose of deriving no-effect-concentration (NEC), no-significant-effect-concentration (NSEC), and effect-concentration (of specified…
sparsegl: An R Package for Estimating Sparse Group Lasso
https://www.jstatsoft.org/index.php/jss/article/view/v110i06
Published: August 29, 2024 00:00
The sparse group lasso is a high-dimensional regression technique that is useful for problems whose predictors have a naturally grouped structure and where sparsity is encouraged at both the group and individual predictor level. In this paper we discuss a…
makemyprior: Intuitive Construction of Joint Priors for Variance Parameters in R
https://www.jstatsoft.org/index.php/jss/article/view/v110i03
Published: August 29, 2024 00:00
Priors allow us to robustify inference and to incorporate expert knowledge in Bayesian hierarchical models. This is particularly important when there are random effects that are hard to identify based on observed data. The challenge lies in understanding…
Extremes.jl: Extreme Value Analysis in Julia
https://www.jstatsoft.org/index.php/jss/article/view/v109i06
Published: June 4, 2024 00:00
The Extremes.jl package provides exhaustive, high-performance functions by leveraging the multiple-dispatch capabilities in Julia for the analysis of extreme values. In particular, the package implements statistical models for both block maxima and…
fHMM: Hidden Markov Models for Financial Time Series in R
https://www.jstatsoft.org/index.php/jss/article/view/v109i09
Published: June 3, 2024 00:00
Hidden Markov models constitute a versatile class of statistical models for time series that are driven by hidden states. In financial applications, the hidden states can often be linked to market regimes such as bearish and bullish markets or recessions…
cpop: Detecting Changes in Piecewise-Linear Signals
https://www.jstatsoft.org/index.php/jss/article/view/v109i07
Published: May 29, 2024 00:00
Changepoint detection is an important problem with a wide range of applications. There are many different types of changes that one may wish to detect, and a widerange of algorithms and software for detecting them. However there are relatively few…
funGp: An R Package for Gaussian Process Regression with Scalar and Functional Inputs
https://www.jstatsoft.org/index.php/jss/article/view/v109i05
Published: May 11, 2024 00:00
This article introduces funGp, an R package which handles regression problems involving multiple scalar and/or functional inputs, and a scalar output, through the Gaussian process model. This is particularly of interest for the design and analysis of…