) # S3 method for class 'lm' cplot ( object, x = attributes ( terms ( object )) ], dx = x, what = c ( 'prediction', 'effect' ), data = prediction :: find_data ( object ), type = c ( 'response', 'link' ), vcov = stats :: vcov ( object ), at, n = 25L, xvals = prediction :: seq_range ( data ], n = n ), level = 0.95, draw = TRUE, xlab = x, ylab = if ( match.arg ( what ) = 'prediction' ) paste0 ( 'Predicted value' ) else paste0 ( 'Marginal effect of ', dx ), xlim = NULL, ylim = NULL, lwd = 1L, col = 'black', lty = 1L, se.type = c ( 'shade', 'lines', 'none' ), se.col = 'black', se.fill = grDevices :: gray ( 0.5, 0.5 ), se.lwd = lwd, se.lty = if ( match.arg ( se.type ) = 'lines' ) 1L else 0L, factor.lty = 0L, factor.pch = 19L, l = se.col, factor.fill = l, factor.cex = 1L, xaxs = 'i', yaxs = xaxs, las = 1L, scatter = FALSE, scatter.pch = 19L, l = se.col, scatter.bg = l, scatter.cex = 0.5, rug = TRUE, rug.col = col, rug.size = -0.02. ) # S3 method for class 'glm' cplot ( object, x = attributes ( terms ( object )) ], dx = x, what = c ( 'prediction', 'effect' ), data = prediction :: find_data ( object ), type = c ( 'response', 'link' ), vcov = stats :: vcov ( object ), at, n = 25L, xvals = prediction :: seq_range ( data ], n = n ), level = 0.95, draw = TRUE, xlab = x, ylab = if ( match.arg ( what ) = 'prediction' ) paste0 ( 'Predicted value' ) else paste0 ( 'Marginal effect of ', dx ), xlim = NULL, ylim = NULL, lwd = 1L, col = 'black', lty = 1L, se.type = c ( 'shade', 'lines', 'none' ), se.col = 'black', se.fill = grDevices :: gray ( 0.5, 0.5 ), se.lwd = lwd, se.lty = if ( match.arg ( se.type ) = 'lines' ) 1L else 0L, factor.lty = 0L, factor.pch = 19L, l = se.col, factor.fill = l, factor.cex = 1L, xaxs = 'i', yaxs = xaxs, las = 1L, scatter = FALSE, scatter.pch = 19L, l = se.col, scatter.bg = l, scatter.cex = 0.5, rug = TRUE, rug.col = col, rug.size = -0.02. ) # S3 method for class 'clm' cplot ( object, x = attributes ( terms ( object )) ], dx = x, what = c ( 'prediction', 'classprediction', 'stackedprediction', 'effect' ), data = prediction :: find_data ( object ), type = c ( 'response', 'link' ), vcov = stats :: vcov ( object ), at, n = 25L, xvals = seq_range ( data ], n = n ), level = 0.95, draw = TRUE, xlab = x, ylab = if ( match.arg ( what ) = 'effect' ) paste0 ( 'Marginal effect of ', dx ) else paste0 ( 'Predicted value' ), xlim = NULL, ylim = if ( match.arg ( what ) %in% c ( 'prediction', 'stackedprediction' )) c ( 0, 1.04 ) else NULL, lwd = 1L, col = 'black', lty = 1L, factor.lty = 1L, factor.pch = 19L, l = col, factor.fill = l, factor.cex = 1L, xaxs = 'i', yaxs = xaxs, las = 1L, scatter = FALSE, scatter.pch = 19L, l = l, scatter.bg = l, scatter.cex = 0.5, rug = TRUE, rug.col = col, rug.size = -0.02.

) # Default S3 method: cplot ( object, x = attributes ( terms ( object )) ], dx = x, what = c ( 'prediction', 'effect' ), data = prediction :: find_data ( object ), type = c ( 'response', 'link' ), vcov = stats :: vcov ( object ), at, n = 25L, xvals = prediction :: seq_range ( data ], n = n ), level = 0.95, draw = TRUE, xlab = x, ylab = if ( match.arg ( what ) = 'prediction' ) paste0 ( 'Predicted value' ) else paste0 ( 'Marginal effect of ', dx ), xlim = NULL, ylim = NULL, lwd = 1L, col = 'black', lty = 1L, se.type = c ( 'shade', 'lines', 'none' ), se.col = 'black', se.fill = grDevices :: gray ( 0.5, 0.5 ), se.lwd = lwd, se.lty = if ( match.arg ( se.type ) = 'lines' ) 1L else 0L, factor.lty = 0L, factor.pch = 19L, l = se.col, factor.fill = l, factor.cex = 1L, xaxs = 'i', yaxs = xaxs, las = 1L, scatter = FALSE, scatter.pch = 19L, l = se.col, scatter.bg = l, scatter.cex = 0.5, rug = TRUE, rug.col = col, rug.size = -0.02.

Cplot change colors r margins