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r-forge
car:Companion to Applied Regression
Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.
Maintained by John Fox. Last updated 5 months ago.
15.38 score 43k scripts 919 dependentspedersen-fisheries-lab
sspm:Spatial Surplus Production Model Framework for Northern Shrimp Populations
Implement a GAM-based (Generalized Additive Models) spatial surplus production model (spatial SPM), aimed at modeling northern shrimp population in Atlantic Canada but potentially to any stock in any location. The package is opinionated in its implementation of SPMs as it internally makes the choice to use penalized spatial gams with time lags. However, it also aims to provide options for the user to customize their model. The methods are described in Pedersen et al. (2022, <https://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2022/2022_062-eng.html>).
Maintained by Valentin Lucet. Last updated 2 months ago.
3 stars 5.28 score 21 scriptspaulnorthrop
exdex:Estimation of the Extremal Index
Performs frequentist inference for the extremal index of a stationary time series. Two types of methodology are used. One type is based on a model that relates the distribution of block maxima to the marginal distribution of series and leads to the semiparametric maxima estimators described in Northrop (2015) <doi:10.1007/s10687-015-0221-5> and Berghaus and Bucher (2018) <doi:10.1214/17-AOS1621>. Sliding block maxima are used to increase precision of estimation. A graphical block size diagnostic is provided. The other type of methodology uses a model for the distribution of threshold inter-exceedance times (Ferro and Segers (2003) <doi:10.1111/1467-9868.00401>). Three versions of this type of approach are provided: the iterated weight least squares approach of Suveges (2007) <doi:10.1007/s10687-007-0034-2>, the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292> and a similar approach of Holesovsky and Fusek (2020) <doi:10.1007/s10687-020-00374-3> that we refer to as D-gaps. For the K-gaps and D-gaps models this package allows missing values in the data, can accommodate independent subsets of data, such as monthly or seasonal time series from different years, and can incorporate information from right-censored inter-exceedance times. Graphical diagnostics for the threshold level and the respective tuning parameters K and D are provided.
Maintained by Paul J. Northrop. Last updated 11 months ago.
block-maximaextremal-indexextremeextreme-value-statisticsextremesinferencemaximasemiparametricsemiparametric-estimationsemiparametric-maxima-estimatorsthetathresholdvaluecpp
4.92 score 11 scripts 5 dependentshaddonm
MQMF:Modelling and Quantitative Methods in Fisheries
Complements the book "Using R for Modelling and Quantitative Methods in Fisheries" ISBN 9780367469894, published in 2021 by Chapman & Hall in their "Using R series". There are numerous functions and data-sets that are used in the book's many practical examples.
Maintained by Malcolm Haddon. Last updated 2 years ago.
ecologyfisherieshaddonquantitative-methodsuncertainty
11 stars 4.14 score 25 scriptsenvisim
BalancedSampling:Balanced and Spatially Balanced Sampling
Select balanced and spatially balanced probability samples in multi-dimensional spaces with any prescribed inclusion probabilities. It contains fast (C++ via Rcpp) implementations of the included sampling methods. The local pivotal method by Grafström, Lundström and Schelin (2012) <doi:10.1111/j.1541-0420.2011.01699.x> and spatially correlated Poisson sampling by Grafström (2012) <doi:10.1016/j.jspi.2011.07.003> are included. Also the cube method (for balanced sampling) and the local cube method (for doubly balanced sampling) are included, see Grafström and Tillé (2013) <doi:10.1002/env.2194>.
Maintained by Anton Grafström. Last updated 5 months ago.
1 stars 3.52 score 53 scripts 1 dependentscran
SemiPar:Semiparametic Regression
Functions for semiparametric regression analysis, to complement the book: Ruppert, D., Wand, M.P. and Carroll, R.J. (2003). Semiparametric Regression. Cambridge University Press.
Maintained by Billy Aung Myint. Last updated 7 years ago.
3.03 score 8 dependentscran
stpm:Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes
Utilities to estimate parameters of the models with survival functions induced by stochastic covariates. Miscellaneous functions for data preparation and simulation are also provided. For more information, see: (i)"Stochastic model for analysis of longitudinal data on aging and mortality" by Yashin A. et al. (2007), Mathematical Biosciences, 208(2), 538-551, <DOI:10.1016/j.mbs.2006.11.006>; (ii) "Health decline, aging and mortality: how are they related?" by Yashin A. et al. (2007), Biogerontology 8(3), 291(302), <DOI:10.1007/s10522-006-9073-3>.
Maintained by Ilya Y. Zhbannikov. Last updated 3 years ago.
2.70 score