plot.mfp function - RDocumentation
plot(x, var=NULL, ref.zero=TRUE, ask=TRUE, ...) object representing a fitted mfp model. the variable for which plots are desired. By default, plots are produced in turn for each variable of a model. subtract a constant from X beta before plotting so that the reference value of the 'x'-variable yields 'y=0'.
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mfp Fit a Multiple Fractional Polynomial Model Description Selects the multiple fractional polynomial (MFP) model which best predicts the outcome. The model may be a generalized linear model or a proportional hazards (Cox) model. Usage mfp(formula, data, family = gaussian, method = c("efron", "breslow"),
R: Multivariable Fractional Polynomial Models with Extensions
plot_mfp: Plot response functions from a fitted 'mfp2' object: predict.mfp2: Predict Method for 'mfp2' Fits: prepare_newdata_for_predict: Helper function to prepare newdata for predict function: print.mfp2: Print method for objects of class 'mfp2' print_mfp_ic_step: Function for verbose printing of function selection procedure (FSP) print_mfp ...
Plot response functions from a fitted mfp2 object - search.r …
Plot response functions from a fitted mfp2 object Description. Plots the partial linear predictors with confidence limits against the selected covariate(s) of interest. Usage
r - Plotting mfp formula in geom_smooth - Stack Overflow
2022年9月15日 · Inside geom_smooth, you can use any method that produces an object which has a predict method, so instead of method = "glm" you can use method = mfp directly - at least in theory. The problem is that mfp doesn't accept a weights argument, but geom_smooth always passes one to the method, even if the weights
mfp2 source: R/fracplot.R - R Package Documentation
Documented in fracplot plot_mfp #' Plot response functions from a fitted `mfp2` object #' #' Plots the partial linear predictors with confidence limits #' against the selected covariate(s) of interest.
mfp function - RDocumentation
Selects the multiple fractional polynomial (MFP) model which best predicts the outcome. The model may be a generalized linear model or a proportional hazards (Cox) model.
mfp source: R/plot.mfp.R - R Package Documentation
plot.mfp <-function (x, var = NULL, ref.zero = TRUE, what = "all", ask = TRUE,...
mfp/R/plot.mfp.R at master · cran/mfp - GitHub
mfp — Multivariable Fractional Polynomials Report bugs for this package: https://github.com/georgheinze/mfp/issues/ - mfp/R/plot.mfp.R at master · cran/mfp :exclamation: This is a read-only mirror of the CRAN R package repository.