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tyee001

VGAM:Vector Generalized Linear and Additive Models

An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.

Maintained by Thomas Yee. Last updated 2 months ago.

fortran

10 stars 10.67 score 3.6k scripts 169 dependents

alexanderrobitzsch

miceadds:Some Additional Multiple Imputation Functions, Especially for 'mice'

Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are implemented. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>), substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>), and features for the generation of synthetic datasets (Reiter, 2005, <doi:10.1111/j.1467-985X.2004.00343.x>; Nowok, Raab, & Dibben, 2016, <doi:10.18637/jss.v074.i11>).

Maintained by Alexander Robitzsch. Last updated 29 days ago.

missing-datamultiple-imputationopenblascpp

16 stars 9.16 score 542 scripts 9 dependents

zeileis

exams:Automatic Generation of Exams in R

Automatic generation of exams based on exercises in Markdown or LaTeX format, possibly including R code for dynamic generation of exercise elements. Exercise types include single-choice and multiple-choice questions, arithmetic problems, string questions, and combinations thereof (cloze). Output formats include standalone files (PDF, HTML, Docx, ODT, ...), Moodle XML, QTI 1.2, QTI 2.1, Blackboard, Canvas, OpenOlat, ILIAS, TestVision, Particify, ARSnova, Kahoot!, Grasple, and TCExam. In addition to fully customizable PDF exams, a standardized PDF format (NOPS) is provided that can be printed, scanned, and automatically evaluated.

Maintained by Achim Zeileis. Last updated 23 hours ago.

1 stars 8.22 score 872 scripts 5 dependents

psyteachr

webexercises:Create Interactive Web Exercises in 'R Markdown' (Formerly 'webex')

Functions for easily creating interactive web pages using 'R Markdown' that students can use in self-guided learning.

Maintained by Lisa DeBruine. Last updated 2 years ago.

interactiveteachingwebsite

32 stars 6.86 score 458 scripts

bbtomas

rPraat:Interface to Praat

Read, write and manipulate 'Praat' TextGrid, PitchTier, Pitch, IntensityTier, Formant, Sound, and Collection files <https://www.fon.hum.uva.nl/praat/>.

Maintained by Tomas Boril. Last updated 3 years ago.

29 stars 6.13 score 156 scripts 2 dependents

jernejjevsenak

dendroTools:Linear and Nonlinear Methods for Analyzing Daily and Monthly Dendroclimatological Data

Provides novel dendroclimatological methods, primarily used by the Tree-ring research community. There are four core functions. The first one is daily_response(), which finds the optimal sequence of days that are related to one or more tree-ring proxy records. Similar function is daily_response_seascorr(), which implements partial correlations in the analysis of daily response functions. For the enthusiast of monthly data, there is monthly_response() function. The last core function is compare_methods(), which effectively compares several linear and nonlinear regression algorithms on the task of climate reconstruction.

Maintained by Jernej Jevsenak. Last updated 1 months ago.

5 stars 6.13 score 81 scripts

trinker

numform:Tools to Format Numbers for Publication

Format numbers and plots for publication; includes the removal of leading zeros, standardization of number of digits, addition of affixes, and a p-value formatter. These tools combine the functionality of several 'base' functions such as 'paste()', 'format()', and 'sprintf()' into specific use case functions that are named in a way that is consistent with usage, making their names easy to remember and easy to deploy.

Maintained by Tyler Rinker. Last updated 3 years ago.

number-formating

51 stars 6.06 score 151 scripts 1 dependents

eriqande

rubias:Bayesian Inference from the Conditional Genetic Stock Identification Model

Implements Bayesian inference for the conditional genetic stock identification model. It allows inference of mixed fisheries and also simulation of mixtures to predict accuracy. A full description of the underlying methods is available in a recently published article in the Canadian Journal of Fisheries and Aquatic Sciences: <doi:10.1139/cjfas-2018-0016>.

Maintained by Eric C. Anderson. Last updated 1 years ago.

noaa-omics-softwarecpp

3 stars 5.90 score 89 scripts

csblatvia

surveyplanning:Survey Planning Tools

Tools for sample survey planning, including sample size calculation, estimation of expected precision for the estimates of totals, and calculation of optimal sample size allocation.

Maintained by Juris Breidaks. Last updated 4 years ago.

sample-sizesamplingstatistics

8 stars 4.53 score 14 scripts 1 dependents

mayamathur

MetaUtility:Utility Functions for Conducting and Interpreting Meta-Analyses

Contains functions to estimate the proportion of effects stronger than a threshold of scientific importance (function prop_stronger), to nonparametrically characterize the distribution of effects in a meta-analysis (calib_ests, pct_pval), to make effect size conversions (r_to_d, r_to_z, z_to_r, d_to_logRR), to compute and format inference in a meta-analysis (format_CI, format_stat, tau_CI), to scrape results from existing meta-analyses for re-analysis (scrape_meta, parse_CI_string, ci_to_var).

Maintained by Maya B. Mathur. Last updated 3 years ago.

3.40 score 21 scripts 2 dependents

dobrowski

MCOE:Creates New Folders and Loads Standard Practices for Monterey County Office of Education

Basic Setup for Projects in R for Monterey County Office of Education. It contains functions often used in the analysis of education data in the county office including seeing if an item is not in a list, rounding in the manner the general public expects, including logos for districts, switching between district names and their county-district-school codes, accessing the local 'SQL' table and making thematically consistent graphs.

Maintained by David Dobrowski. Last updated 1 years ago.

1 stars 3.11 score 26 scripts

drelliesmall

smallstuff:Dr. Small's Functions

Functions used in courses taught by Dr. Small at Drew University.

Maintained by Ellie Small. Last updated 1 years ago.

1.48 score 2 scripts 1 dependents

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