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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'.

The mfp package is a collection of R (R Core Team 2022) functions targeted at the use of fractional polynomials (FP) for modelling the influence of continuous covariates on the outcome in regression models, as introduced by Royston and Altman (1994) and modified by Sauerbrei and Royston (1999). The model may include binary, categorical or ...

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2006年8月1日 · Function plot.mfp draws two specific plots: (i) the linear predictor function, (ii) a plot of the partial residuals together with a lowess smooth. For mfp objects inheriting from coxph smoothed martingale-based residuals of the null model are drawn additionally to support the investigation of the functional form of the linear predictor.

Micro Food Plots is a business that offers the avid hunter equipment to aid them in creating an ideal food plot for hunting.

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.

plot.mfp <-function (x, var = NULL, ref.zero = TRUE, what = "all", ask = TRUE,...

Plots the partial linear predictors with confidence limits against the selected covariate(s) of interest.