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disaggregation (version 0.4.0)

Disaggregation Modelling

Description

Fits disaggregation regression models using 'TMB' ('Template Model Builder'). When the response data are aggregated to polygon level but the predictor variables are at a higher resolution, these models can be useful. Regression models with spatial random fields. The package is described in detail in Nandi et al. (2023) .

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Version

Install

install.packages('disaggregation')

Monthly Downloads

247

Version

0.4.0

License

MIT + file LICENSE

Maintainer

Tim Lucas

Last Published

October 2nd, 2024

Functions in disaggregation (0.4.0)

make_model_object

Create the TMB model object for the disaggregation model

Fit the disaggregation model

print.disag_data

Print function for disaggregation input data

Function to predict mean from the model result

Roxygen commands

summary.disag_model

Summary function for disaggregation fit result

print.disag_prediction

Print function for disaggregation prediction

summary.disag_data

Summary function for disaggregation input data

Build mesh for disaggregaton model

Prepare data for disaggregation modelling

summary.disag_prediction

Summary function for disaggregation prediction

Function to fit the disaggregation model

print.disag_model

Print function for disaggregation fit result.

plot.disag_model

Plot results of fitted model

plot.disag_data

Plot input data for disaggregation

getCovariateRasters

Get a SpatRaster of covariates from a folder containing .tif files

Extract polygon id and response data into a data.frame from a sf object

predict.disag_model

Predict mean and uncertainty from the disaggregation model result

getStartendindex

Function to match pixels to their corresponding polygon

plot.disag_prediction

Plot mean and uncertainty predictions from the disaggregation model results

plot_disag_model_data

Convert results of the model ready for plotting

predict_uncertainty

Function to predict uncertainty from the model result