guhjy Goto Github PK

mvinfluence

Influence Measures and Diagnostic Plots for Multivariate Linear Models

mvnfast

Fast methods for multivariate normal distributions

mvot

code for "A Likelihood-based Approach for Multivariate One-Sided Tests With Missing Data"

mvtboost

Boosted regression trees for multivariate, longitudinal, and hierarchically clustered data.

mw

Simulation scripts for matching weights in three-group studies

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

mycor

myellipsefit

Convenience package using conicfit to calculate an elliptic fit to data. Provides ellipsis parameters (axes, angle, area, and more). Provides a ggplot2 layer as well.

mypkglib

:computer: convenience scripts for easily setting up package libraries

naniar

Tidy data structures, summaries, and visualisations for missing data

navdata

Network Analysis and Visualization Data

networkcomparisontest

Statistical comparison of two networks with respect to global strength

ngme

Linear Mixed-Effects Models for Non-Gaussian Repeated Measurement Data

nhanes

R package containing versions of NHANES data

nhanes-1

Some scripts for the analysis of data from the National Health and Nutrition Examination Survey (NHANES).

nhanes-2

Scripts to download and aggregate NHANES data

nhanes-diabetes

An ensemble model for predicting diabetes onset using NHANES Data

nhanes.tools

R package to make loading and using NHANES data easier

nhanes_presentation

Demo of analyzing NHANES with RNHANES

nhanes_scraper

scripts to scrape NHANES doc files

nhanesml

ML on NHANES nutrition data

nima

:hammer: R/nima: A package comprising Nima Hejazi's personal R toolbox

nlinteraction

R package to implement nonlinear, interaction models with variable selection

nlpred

Estimators of cross-validated prediction metrics with improved small sample performance

non_parametric

This is the R code for several common non-parametric methods (kernel est., mean regression, quantile regression, boostraps) with both practical applications on data and simulations

nonconformist

Python implementation of the conformal prediction framework.

normal-uniform-and-exponential-distributions-simulations

This is a project I did in the Spring of 2017 for a graduate course in Statistical Computing. I was asked to find the descriptive statistics of 1000 simulations of a distribution, specifically to find the mean, median, midrange, and interquartile range of the simulations. I was asked to find these statistics for 1000 simulations of sample sizes of 10, 30, and 100. I was aslo asked to find each of these sample sizes for Normal, Uniform, and Exponential distributions.

nothing

A package about nothing

npcausal

npci

Non-parametrics for Causal Inference