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: 2026-10-14 11:58:27 UTC; root
Author: Chris Rohlfs [aut, cre]
        (<https://orcid.org/0000-0001-7714-9231>)
Maintainer: Chris Rohlfs <car2228@columbia.edu>
Repository: https://carohlfs.r-universe.dev
Date/Publication: 2022-09-09 07:20:02 UTC
RemoteUrl: https://github.com/cran/moose
RemoteRef: HEAD
RemoteSha: 84e8df2263ae9c0c70d8ce7d296d5f0d8e84f2ff