Package: moose
Title: Mean Squared Out-of-Sample Error Projection
Version: 0.0.1
Authors@R: 
    person("Chris", "Rohlfs", , "car2228@columbia.edu", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-7714-9231"))
Description: Projects mean squared out-of-sample error for a linear regression based upon the methodology developed in Rohlfs (2022) <doi:10.48550/arXiv.2209.01493>.  It consumes as inputs the lm object from an estimated OLS regression (based on the "training sample") and a data.frame of out-of-sample cases (the "test sample") that have non-missing values for the same predictors. The test sample may or may not include data on the outcome variable; if it does, that variable is not used. The aim of the exercise is to project what what mean squared out-of-sample error can be expected given the predictor values supplied in the test sample. Output consists of a list of three elements: the projected mean squared out-of-sample error, the projected out-of-sample R-squared, and a vector of out-of-sample "hat" or "leverage" values, as defined in the paper.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.2.1
NeedsCompilation: no
Packaged: 2022-09-09 00:07:54 UTC; chris
Author: Chris Rohlfs [aut, cre] (<https://orcid.org/0000-0001-7714-9231>)
Maintainer: Chris Rohlfs <car2228@columbia.edu>
Repository: CRAN
Date/Publication: 2022-09-09 08:20:02 UTC
Built: R 4.6.0; ; 2026-04-26 22:29:45 UTC; unix
