R/blr-blorr.R

In blorr: Tools for Developing Binary Logistic Regression Models

#' \code{blorr} package
#'
#' Tools for developing binary logistic regression models
#'
#' See the README on
#' \href{https://github.com/rsquaredacademy/blorr}{GitHub}
#'
#' @docType package
#' @name blorr
NULL

## quiets concerns of R CMD check re: the .'s that appear in pipelines
if (getRversion() >= "2.15.1") {
  utils::globalVariables(c(
    ".", "n", "data",
    "converged", "model_info", "log_lik", "df.null", "value", "value1", "prob",
    "decile", "response", "total", "1", "0", "cum_total", "cum_1s", "cum_0s",
    "cum_1s_%", "cum_0s_%", "tp", "tn", "fp", "fn", "sensitivity",
    "specificity", "1 - specificity", "sensitivity_per", "no", "yes", "total",
    "dist_yes", "dist_no", "dist_diff", "woe", "iv", "distribution", "approval",
    "gains_table", "cum_total_per", "cum_1s_per", "cum_total_y", "y",
    "fitted.values", "response", "fit_val", "0s_expected", "0s_observed", "1s",
    "1s%", "1s_expected", "1s_observed", "2.5 %", "97.5 %", "ann_loc",
    "ann_locate", "avg_prob", "cum_0s_per", "cum_total_%", "d_f", "dist_table",
    "group", "honcomp", "ks", "lr_ratio", "n%", "negative", "p_value",
    "positive", "predict", "predicted", "prob_n", "sec", "test_result",
    "variable", "woe_iv_table", "chisq_stat", "confusion_matrix",
    "partition_table", "segment_data", "var_name", "fit", "resid", "cbar",
    "dev_df", "difchisq", "difdev", "fitted", "hat", "lr_df", "mfit",
    "twoway_segment", "varnames", "color", "concordance", "concordant",
    "d_by_g_mean","dbetas", "decile_mean", "discordant", "gmean", "obs",
    "pairs", "tied", "ties", "txt"
  ))
}