`weitrix_calplot.Rd`

Various plots based on weighted squared residuals
of each element in the weitrix.
`weight*residual^2`

is the Pearson residual for a gamma GLM plus one,
as used by `weitrix_calibrate_all`

.

weitrix_calplot( weitrix, design = ~1, covar, cat, funnel = FALSE, guides = TRUE )

weitrix | A weitrix object, or an object that can be converted to a weitrix
with |
---|---|

design | A formula in terms of |

covar | Optional. A covariate. Specify as you would with |

cat | Optional. A categorical variable to break down the data by.
Specify as you would with |

funnel | Flag. Produce a funnel plot?
Note: |

guides | Show blue guide lines. |

A ggplot2 plot.

This function is not memory efficient. It is suitable for typical bulk data, but generally not not for single-cell.

Defaults to a boxplot of sqrt(weight) weighted residuals. Blue guide bars are shown for the expected quartiles, these will ideally line up with the boxplot.

If `cat`

is given, it will be used to break the elements down
into categories.

If `covar`

is given, sqrt(weight) weighted residuals are plotted versus
the covariate, with red trend lines for
the mean and for the mean +/- one standard deviation.
If the weitrix is calibrated, the trend lines should be horizontal lines
with y intercept close to -1, 0 and 1.
Blue guide lines are shown for this ideal outcome.

Any of the variables available with `weitrix_calibrate_all`

can be used for `covar`

or `cat`

.

weitrix_calplot(simwei, ~1)weitrix_calplot(simwei, ~1, covar=mu)weitrix_calplot(simwei, ~1, cat=col)# weitrix_calplot should generally be used after calibration cal <- weitrix_calibrate_all(simwei, ~1, ~col+log(weight)) weitrix_calplot(cal, ~1, cat=col)# You can use a matrix of the same size as the weitrix as a covariate. # It will often be useful to assess vs the original weighting. weitrix_calplot(cal, ~1, covar=weitrix_weights(simwei))