Estimation in Optimal Adaptive Two-Stage Designs

Methods to evaluate the performance characteristics of various point and interval estimators for optimal adaptive two-stage designs as described in Meis et al. (2024) . Specifically, this package is written to work with trial designs created by the 'adoptr' package (Kunzmann et al. (2021) ; Pilz et al. (2021) )). Apart from the a priori evaluation of performance characteristics, this package also allows for the evaluation of the implemented estimators on real datasets, and it implements methods to calculate p-values.

Big Data Statistical Analysis for High-Dimensional Models

Big data statistical analysis for high-dimensional models is made possible by modifying lasso.proj() in 'hdi' package by replacing its nodewise-regression with sparse precision matrix computation using 'BigQUIC'.

A Toolbox for Writing Pretty Papers and Reports

A toolbox for writing 'knitr', 'Sweave' or other 'LaTeX'- or 'markdown'-based reports and to prettify the output of various estimated models.

Estimation of Order of Mixture Distributions

Methods for estimating the order of a mixture model. The approaches considered are based on the following papers (extensive list of references is available in the vignette): 1. Dacunha-Castelle, Didier, and Elisabeth Gassiat. The estimation of the order of a mixture model. Bernoulli 3, no. 3 (1997): 279-299. < https://projecteuclid.org/download/pdf_1/euclid.bj/1177334456>. 2. Woo, Mi-Ja, and T. N. Sriram. Robust estimation of mixture complexity. Journal of the American Statistical Association 101, no. 476 (2006): 1475-1486. . 3. Woo, Mi-Ja, and T. N. Sriram. Robust estimation of mixture complexity for count data. Computational statistics & data analysis 51, no. 9 (2007): 4379-4392. . 4. Umashanger, T., and T. N. Sriram. L2E estimation of mixture complexity for count data. Computational statistics & data analysis 53, no. 12 (2009): 4243-4254. . 5. Karlis, Dimitris, and Evdokia Xekalaki. On testing for the number of components in a mixed Poisson model. Annals of the Institute of Statistical Mathematics 51, no. 1 (1999): 149-162. . 6. Cutler, Adele, and Olga I. Cordero-Brana. Minimum Hellinger Distance Estimation for Finite Mixture Models. Journal of the American Statistical Association 91, no. 436 (1996): 1716-1723. . A number of datasets are included. 1. accidents, from Karlis, Dimitris, and Evdokia Xekalaki. On testing for the number of components in a mixed Poisson model. Annals of the Institute of Statistical Mathematics 51, no. 1 (1999): 149-162. . 2. acidity, from Sybil L. Crawford, Morris H. DeGroot, Joseph B. Kadane & Mitchell J. Small (1992) Modeling Lake-Chemistry Distributions: Approximate Bayesian Methods for Estimating a Finite-Mixture Model, Technometrics, 34:4, 441-453. . 3. children, from Thisted, R. A. (1988). Elements of statistical computing: Numerical computation (Vol. 1). CRC Press. 4. faithful, from R package "datasets"; Azzalini, A. and Bowman, A. W. (1990). A look at some data on the Old Faithful geyser. Applied Statistics, 39, 357--365. < https://www.jstor.org/stable/2347385>. 5. shakespeare, from Efron, Bradley, and Ronald Thisted. "Estimating the number of unseen species: How many words did Shakespeare know?." Biometrika 63.3 (1976): 435-447. .

Generalized Additive Latent and Mixed Models

Estimates generalized additive latent and mixed models using maximum marginal likelihood, as defined in Sorensen et al. (2023) , which is an extension of Rabe-Hesketh and Skrondal (2004)'s unifying framework for multilevel latent variable modeling . Efficient computation is done using sparse matrix methods, Laplace approximation, and automatic differentiation. The framework includes generalized multilevel models with heteroscedastic residuals, mixed response types, factor loadings, smoothing splines, crossed random effects, and combinations thereof. Syntax for model formulation is close to 'lme4' (Bates et al. (2015) ) and 'PLmixed' (Rockwood and Jeon (2019) ).

Fast Kernel Density Estimation with Hexagonal Grid

Kernel density estimation with hexagonal grid for bivariate data. Hexagonal grid has many beneficial properties like equidistant neighbours and less edge bias, making it better for spatial analyses than the more commonly used rectangular grid. Carr, D. B. et al. (1987) . Diggle, P. J. (2010) . Hill, B. (2017) < https://blog.bruce-hill.com/meandering-triangles>. Jones, M. C. (1993) .

Bessel Functions Rcpp Interface

Exports an 'Rcpp' interface for the Bessel functions in the 'Bessel' package, which can then be called from the 'C++' code of other packages. For the original 'Fortran' implementation of these functions see Amos (1995) .

Optimized Automated Gaussian Mixture Assessment

Necessary functions for optimized automated evaluation of the number and parameters of Gaussian mixtures in one-dimensional data. Various methods are available for parameter estimation and for determining the number of modes in the mixture. A detailed description of the methods ca ben found in Lotsch, J., Malkusch, S. and A. Ultsch. (2022) .

Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'

With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.

R Fortunes

A collection of fortunes from the R community.