solve_biascorr.poisson: Bias correction solver for Poisson type problems

In tkrisztin/downscalr: Downscaling land-use change projections

Bias correction solver for Poisson type problems

Description

Bias correction solver for Poisson type problems

Usage

solve_biascorr.poisson(targets, xmat, betas, options = downscale_control_pop())

Arguments

targets	A dataframe with columns pop.type and value (all targets >= 0)
xmat	A dataframe of explanatory variables with columns ks and value.
betas	A dataframe of coefficients with columns ks, lu.from, lu.to & value
options	A list with solver options. Call downscale_control_pop for default options and for more detail.

Details

Given J targets matches the projections from a Poisson-type model.

You should not call this functions directly, call downscale_pop instead.

Targets should be specified in a dataframe with a pop.type and a value column. All targets must be larger or equal to zero.

Value

A list containing

• out.res A n x p matrix of area allocations

• out.solver A list of the solver output

Examples

## A basic example

tkrisztin/downscalr documentation built on June 2, 2025, 1:16 a.m.