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easystats
insight:Easy Access to Model Information for Various Model Objects
A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Maintained by Daniel Lüdecke. Last updated 1 days ago.
easystatshacktoberfestinsightmodelsnamespredictorsrandom
414 stars 17.39 score 568 scripts 214 dependentsjacolien
itsadug:Interpreting Time Series and Autocorrelated Data Using GAMMs
GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) as implemented in the R package 'mgcv' (Wood, S.N., 2006; 2011) is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).
Maintained by Jacolien van Rij. Last updated 3 years ago.
1 stars 6.45 score 576 scripts 2 dependentsnoaa-fims
FIMS:The Fisheries Integrated Modeling System
The Fisheries Integrated Modeling System is a next-generation framework of stock assessment models, assisting fishery managers with the goal of achieving sustainable fisheries. This system, when completed in a few years, offers the NOAA Fisheries and global fisheries science communities an advanced set of stock assessment models. These tools can be used separately or in combination to incorporate ecosystem and socioeconomic data and models, as well as climate effects and other drivers within the marine environment, into stock assessment models.
Maintained by Kelli F. Johnson. Last updated 2 months ago.
23 stars 5.67 score 24 scriptshenry-heppe
adproclus:Additive Profile Clustering Algorithms
Obtain overlapping clustering models for object-by-variable data matrices using the Additive Profile Clustering (ADPROCLUS) method. Also contains the low dimensional ADPROCLUS method for simultaneous dimension reduction and overlapping clustering. For reference see Depril, Van Mechelen, Mirkin (2008) <doi:10.1016/j.csda.2008.04.014> and Depril, Van Mechelen, Wilderjans (2012) <doi:10.1007/s00357-012-9112-5>.
Maintained by Henry Heppe. Last updated 7 months ago.
2 stars 3.60 score 2 scripts