@@ -14,19 +14,21 @@
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#' An object of class \code{"ols_step_all_possible"} is a data frame containing the
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#' following components:
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#'
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#' \item{mindex}{model index}
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#' \item{n}{model number}
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#' \item{predictors}{predictors in the model}
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#' \item{rsquare}{rsquare of the model}
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#' \item{adjr}{adjusted rsquare of the model}
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#' \item{rmse}{root mean squared error of the model}
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#' \item{predrsq}{predicted rsquare of the model}
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#' \item{cp}{mallow's Cp}
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#' \item{aic}{akaike information criteria}
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#' \item{sbic}{sawa bayesian information criteria}
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#' \item{sbc}{schwarz bayes information criteria}
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#' \item{gmsep}{estimated MSE of prediction, assuming multivariate normality}
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#' \item{jp}{final prediction error}
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#' \item{pc}{amemiya prediction criteria}
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#' \item{sp}{hocking's Sp}
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#' \item{msep}{estimated MSE of prediction, assuming multivariate normality}
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#' \item{fpe}{final prediction error}
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#' \item{apc}{amemiya prediction criteria}
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#' \item{hsp}{hocking's Sp}
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#'
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#' @references
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#' Mendenhall William and  Sinsich Terry, 2012, A Second Course in Statistics Regression Analysis (7th edition).
@@ -65,6 +67,7 @@
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    predictors = unlist(metrics$preds),
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    rsquare    = unlist(metrics$rsq),
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    adjr       = unlist(metrics$adjrsq),
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    rmse       = unlist(metrics$rmse),
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    predrsq    = unlist(metrics$predrsq),
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    cp         = unlist(metrics$cp),
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    aic        = unlist(metrics$aic),
@@ -156,10 +159,10 @@
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  if (print_plot) {
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    marrangeGrob(myplots, nrow = 2, ncol = 2)
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  } else {
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    return(myplots)
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  }
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  return(myplots)
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}
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#' All possible regression plot
@@ -366,6 +369,7 @@
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  mcount    <- 0
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  rsq       <- list()
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  adjrsq    <- list()
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  sigma     <- list()
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  predrsq   <- list()
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  cp        <- list()
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  aic       <- list()
@@ -393,6 +397,7 @@
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      lpreds[mcount]    <- lp
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      rsq[[mcount]]     <- out$rsq
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      adjrsq[[mcount]]  <- out$adjr
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      sigma[[mcount]]   <- out$sigma
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      predrsq[[mcount]] <- ols_pred_rsq(out$model)
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      cp[[mcount]]      <- ols_mallows_cp(out$model, model)
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      aic[[mcount]]     <- ols_aic(out$model)
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  }
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  result <- list(
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    lpreds = lpreds, rsq = rsq, adjrsq = adjrsq,
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    lpreds = lpreds, rsq = rsq, adjrsq = adjrsq, rmse = sigma,
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    predrsq = predrsq, cp = cp, aic = aic, sbic = sbic,
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    sbc = sbc, msep = msep, fpe = fpe, apc = apc, hsp = hsp,
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    preds = preds, lc = lc, q = q, t = t, betas = betas
Files Coverage
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src 100.00%
Project Totals (52 files) 92.81%
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