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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "moose" in publications use:'
type: software
license: MIT
title: 'moose: Mean Squared Out-of-Sample Error Projection'
version: 0.0.1
doi: 10.32614/CRAN.package.moose
abstract: 'Projects mean squared out-of-sample error for a linear regression based
  upon the methodology developed in Rohlfs (2022) <https://doi.org/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.'
authors:
- family-names: Rohlfs
  given-names: Chris
  email: car2228@columbia.edu
  orcid: https://orcid.org/0000-0001-7714-9231
repository: https://carohlfs.r-universe.dev
commit: 84e8df2263ae9c0c70d8ce7d296d5f0d8e84f2ff
date-released: '2022-09-09'
contact:
- family-names: Rohlfs
  given-names: Chris
  email: car2228@columbia.edu
  orcid: https://orcid.org/0000-0001-7714-9231