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Articles 1 - 7 of 7
Full-Text Articles in Statistical Models
A Course In Data Science: R And Prediction Modeling, Adam Kapelner
A Course In Data Science: R And Prediction Modeling, Adam Kapelner
Open Educational Resources
This is a self-contained course in data science and machine learning using R. It covers philosophy of modeling with data, prediction via linear models, machine learning including support vector machines and random forests, probability estimation and asymmetric costs using logistic regression and probit regression, underfitting vs. overfitting, model validation, handling missingness and much more. There is formal instruction of data manipulation using dplyr and data.table, visualization using ggplot2 and statistical computing.
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematics Ancillary Materials
This collection of student and instructor materials for Mathematical Modeling contains lesson plans, lecture slides, homework, learning goals, and student notes for the following major topics:
- Linear Functions
- Quadratic Functions
- Exponential Functions
- Logarithmic Functions
This is a materials update for a collection of materials created for a Round Nine ALG Textbook Transformation Grant.
Garma Toolbox For Matlab, Mehdi Jalalpour
Glme3_Ado_Do_Files, Joseph Hilbe
Nbr2 Stata Ado-Do Files, Joseph Hilbe
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Michael Stanley Smith
This is an example Windows 32bit program to estimate a Gaussian copula model with NBD margins. The margins are estimated first using MLE, and the copula second using Bayesian MCMC. The model was discussed in Danaher & Smith (2011; Marketing Science) as example 4 (section 4.2).
Poicen.Sas : Censored Poisson Regression, Joseph Hilbe, Gordon Johnston
Poicen.Sas : Censored Poisson Regression, Joseph Hilbe, Gordon Johnston
Joseph M Hilbe
SAS Macro to estimate censored Poisson data, using method of Hilbe. See Hilbe, Joseph M (2011), Negative Binomial Regression, 2nd ed (Cambridge University Press)