PredictorResponseBivar: Predict the exposure-response function at a new grid of...

Description Usage Arguments Details

Description

Predict the exposure-response function at a new grid of points

Usage

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PredictorResponseBivar(fit, y = NULL, Z = NULL, X = NULL,
  z.pairs = NULL, method = "approx", ngrid = 50, q.fixed = 0.5,
  sel = NULL, min.plot.dist = 0.5, center = TRUE, z.names = colnames(Z),
  verbose = TRUE, ...)

Arguments

fit

An object containing the results returned by a the kmbayes function

y

a vector of outcome data of length n.

Z

an n-by-M matrix of predictor variables to be included in the h function. Each row represents an observation and each column represents an predictor.

X

an n-by-K matrix of covariate data where each row represents an observation and each column represents a covariate. Should not contain an intercept column.

z.pairs

data frame showing which pairs of pollutants to plot

method

method for obtaining posterior summaries at a vector of new points. Options are "approx" and "exact"; defaults to "approx", which is faster particularly for large datasets; see details

ngrid

number of grid points in each dimension

q.fixed

vector of quantiles at which to fix the remaining predictors in Z

sel

logical expression indicating samples to keep; defaults to keeping the second half of all samples

min.plot.dist

specifies a minimum distance that a new grid point needs to be from an observed data point in order to compute the prediction; points further than this will not be computed

center

flag for whether to scale the exposure-response function to have mean zero

z.names

optional vector of names for the columns of z

verbose

TRUE or FALSE: flag of whether to print intermediate output to the screen

...

other argumentd to pass on to the prediction function

Details

For guided examples, go to https://jenfb.github.io/bkmr/overview.html



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