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harrelfe
Hmisc:Harrell Miscellaneous
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.
Maintained by Frank E Harrell Jr. Last updated 5 days ago.
209 stars 17.64 score 17k scripts 750 dependents
fcheysson
hawkesbow:Estimation of Hawkes Processes from Binned Observations
Implements an estimation method for Hawkes processes when count data are only observed in discrete time, using a spectral approach derived from the Bartlett spectrum, see Cheysson and Lang (2020) <arXiv:2003.04314>. Some general use functions for Hawkes processes are also included: simulation of (in)homogeneous Hawkes process, maximum likelihood estimation, residual analysis, etc.
Maintained by Felix Cheysson. Last updated 1 years ago.
7 stars 4.54 score 4 scripts
paulnorthrop
smovie:Some Movies to Illustrate Concepts in Statistics
Provides movies to help students to understand statistical concepts. The 'rpanel' package <https://cran.r-project.org/package=rpanel> is used to create interactive plots that move to illustrate key statistical ideas and methods. There are movies to: visualise probability distributions (including user-supplied ones); illustrate sampling distributions of the sample mean (central limit theorem), the median, the sample maximum (extremal types theorem) and (the Fisher transformation of the) product moment correlation coefficient; examine the influence of an individual observation in simple linear regression; illustrate key concepts in statistical hypothesis testing. Also provided are dpqr functions for the distribution of the Fisher transformation of the correlation coefficient under sampling from a bivariate normal distribution.
Maintained by Paul J. Northrop. Last updated 1 years ago.
central-limit-theoremcorrelation-coefficientextremal-types-theoremextremeshypothesis-testinglikelihood-ratio-testlinear-regressionlog-likelihoodmovieprobability-distributionsregressionscore-teststatistical-conceptsstatisticsstatistics-learningteachingteaching-materialstest-statisticwald-test
1 stars 3.70 score 10 scripts