predint_plot: Prediction intervals for functional quantile regression
In marcopalma3/neurofundata: Functional data analysis tools for neuroimaging data
Description
Usage
Arguments
Author(s)
Description
Return point predictions and prediction intervals for functional
scalar-on-image quantile regression and outputs from FPCA.
Usage
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predint_plot(
pred_interval,
col = c("#009E73", "gold3", "#D55E00"),
xlab_input = "Difference from chronological age",
ylab_input = "Subjects"
)
Arguments
pred_interval
rownames of data_projected_name used to fit the FPCA
col
rownames of data_projected_name for which to get the FPCA scores
xlab_input
text file with the smoothing projections for each statistical unit
ylab_input
demographic data with the scalar outcome of interest
Author(s)
Marco Palma, M.Palma@warwick.ac.uk
marcopalma3/neurofundata documentation built on Dec. 12, 2019, 5:29 a.m.
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Description Usage Arguments Author(s)
Description
Return point predictions and prediction intervals for functional scalar-on-image quantile regression and outputs from FPCA.
Usage
1 2 3 4 5 6 | predint_plot(
pred_interval,
col = c("#009E73", "gold3", "#D55E00"),
xlab_input = "Difference from chronological age",
ylab_input = "Subjects"
)
|
Arguments
pred_interval |
rownames of |
col |
rownames of |
xlab_input |
text file with the smoothing projections for each statistical unit |
ylab_input |
demographic data with the scalar outcome of interest |
Author(s)
Marco Palma, M.Palma@warwick.ac.uk
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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