feat: model anova

Author: aravindhebbali

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(ols_anova,default)
 S3method(ols_coll_diag,default)
 S3method(ols_correlations,default)
 S3method(ols_model_performance,default)
@@ -52,6 +53,7 @@ S3method(plot,ols_step_forward_p)
 S3method(plot,ols_step_forward_r2)
 S3method(plot,ols_step_forward_sbc)
 S3method(plot,ols_step_forward_sbic)
+S3method(print,ols_anova)
 S3method(print,ols_coll_diag)
 S3method(print,ols_correlations)
 S3method(print,ols_model_performance)
@@ -83,6 +85,7 @@ S3method(print,ols_test_f)
 S3method(print,ols_test_normality)
 S3method(print,ols_test_score)
 export(ols_aic)
+export(ols_anova)
 export(ols_apc)
 export(ols_coll_diag)
 export(ols_correlations)

R/ols-anova.R

@@ -0,0 +1,73 @@
+#' ANOVA
+#'
+#' ANOVA for regression model.
+#'
+#' @param model An object of class \code{lm}.
+#' @param ... Other arguments.
+#'
+#' @return \code{ols_anova} returns an object of class \code{"ols_anova"}.
+#' An object of class \code{"ols_anova"} is a list containing the following
+#' components:
+#'
+#' \item{error_df}{residual degrees of freedom}
+#' \item{model_df}{regression degrees of freedom}
+#' \item{total_df}{total degrees of freedom}
+#' \item{ess}{error sum of squares}
+#' \item{rss}{regression sum of squares}
+#' \item{tss}{total sum of squares}
+#' \item{rms}{regression mean square}
+#' \item{ems}{error mean square}
+#' \item{f}{f statistis}
+#' \item{p}{p-value for \code{f}}
+#'
+#' @examples
+#' # model
+#' model <- lm(mpg ~ disp + hp + wt, data = mtcars)
+#'
+#' # anova
+#' ols_anova(model)
+#'
+#' @export
+#'
+ols_anova <- function(model, ...) UseMethod("ols_anova")
+
+#' @export
+#'
+ols_anova.default <- function(model, ...) {
+  anovam   <- anova(model)
+  n        <- length(anovam$Df)
+  error_df <- anovam$Df[n]
+  model_df <- sum(anovam$Df) - error_df
+  total_df <- sum(anovam$Df)
+  ess      <- anovam$`Sum Sq`[n]
+  tss      <- sum(anovam$`Sum Sq`)
+  rss      <- tss - ess
+  rms      <- rss / model_df
+  ems      <- ess / error_df
+  f        <- rms / ems
+  p        <- pf(f, model_df, error_df, lower.tail = F)
+
+  result <-
+    list(
+      error_df = error_df,
+      model_df = model_df,
+      total_df = total_df,
+      ess      = ess,
+      rss      = rss,
+      tss      = tss,
+      rms      = rms,
+      ems      = ems,
+      f        = f,
+      p        = p
+    )
+
+  class(result) <- "ols_anova"
+
+  return(result)
+}
+
+#' @export
+#'
+print.ols_anova <- function(x, ...) {
+  print_anova(x)
+}

R/output.R

@@ -823,3 +823,65 @@ print_model_perf <- function(data) {
     "RMSE: Root Mean Square Error", "\n\n")
 
 }
+
+print_anova <- function(data) {
+  w7 <- nchar("Regression")
+
+  w8 <- max(
+    nchar("Squares"), nchar(format(round(data$rss, 3), nsmall = 3)),
+    nchar(format(round(data$ess, 3), nsmall = 3)),
+    nchar(format(round(data$tss, 3), nsmall = 3))
+  )
+
+  w9 <- max(
+    nchar("DF"), nchar(format(round(data$model_df, 3), nsmall = 3)),
+    nchar(format(round(data$error_df, 3), nsmall = 3)),
+    nchar(format(round(data$total_df, 3), nsmall = 3))
+  )
+
+  w10 <- max(
+    nchar("Mean Square"),
+    nchar(format(round(data$rms, 3), nsmall = 3)),
+    nchar(format(round(data$ems, 3), nsmall = 3))
+  )
+
+  w11 <- max(nchar("F"), nchar(format(round(data$f, 3), nsmall = 3)))
+  w12 <- max(nchar("Sig."), nchar(format(round(data$p, 3), nsmall = 4)))
+  w <- sum(w7, w8, w9, w10, w11, w12, 21)
+
+  p <- format(round(data$p, 4), nsmall = 4)
+
+  cat(fc("ANOVA", w), "\n")
+  cat(rep("-", w), sep = "", "\n")
+
+  cat(fg("", w7), fs(), fg("Sum of", w8), fs(), fg("", w9), fs(), fg("", w10),
+    fs(), fg("", w11), fs(), fg("", w12), "\n")
+
+  cat(fg("", w7), fs(), fg("Squares", w8), fs(), fg("DF", w9), fs(),
+    fg("Mean Square", w10), fs(), fc("F", w11), fs(), fg("Sig.", w12), "\n")
+
+  cat(rep("-", w), sep = "", "\n")
+
+  cat(
+    fl("Regression", w7), fs(), fg(format(round(data$rss, 3), nsmall = 3), w8),
+    fs(), fg(round(data$model_df, 3), w9), fs(),
+    fg(format(round(data$rms, 3), nsmall = 3), w10), fs(),
+    fg(round(data$f, 3), w11), fs(), fg(p, w12), "\n"
+  )
+
+  cat(
+    fl("Residual", w7), fs(), fg(format(round(data$ess, 3), nsmall = 3), w8),
+    fs(), fg(round(data$error_df, 3), w9), fs(),
+    fg(format(round(data$ems, 3), nsmall = 3), w10), fs(), fg("", w11), fs(),
+    fg("", w12), "\n"
+  )
+
+  cat(
+    fl("Total", w7), fs(), fg(format(round(data$tss, 3), nsmall = 3), w8), fs(),
+    fg(round(data$total_df, 3), w9), fs(), fg("", w10), fs(),
+    fg("", w11), fs(), fg("", w12), "\n"
+  )
+
+  cat(rep("-", w), sep = "", "\n\n")
+
+}

_pkgdown.yml

@@ -63,6 +63,7 @@ reference:
 
     contents:
       - ols_regress
+      - ols_anova
 
   - title: Model Performance
 

docs/reference/index.html

@@ -0,0 +1,16 @@
+# ols_anova prints the expected output
+
+    Code
+      ols_anova(model)
+    Output
+                                     ANOVA                                 
+      --------------------------------------------------------------------
+                      Sum of                                              
+                     Squares        DF    Mean Square      F         Sig. 
+      --------------------------------------------------------------------
+      Regression     931.057         3        310.352    44.566    0.0000 
+      Residual       194.991        28          6.964                     
+      Total         1126.047        31                                    
+      --------------------------------------------------------------------
+      
+