disaggregate_positive: Disaggregation function for strictly positive covariates

In rts2: Real-Time Disease Surveillance

Disaggregation function for strictly positive covariates

Description

Pycnophylactic disaggregation with spatial smoothness on rates

Usage

disaggregate_positive(
  W,
  y_r,
  pop,
  adj,
  lambda_smooth = 1,
  lambda_entropy = 0,
  weights = NULL
)

Arguments

W	m x n aggregation matrix
y_r	length m vector (observed regional counts)
pop	length n vector (population per cell)
adj	n x n adjacency matrix (1 if neighbours, 0 otherwise) or a sparse Matrix from the Matrix package
lambda_smooth	weight on spatial smoothness
lambda_entropy	weight on entropy (0 = pure QP, >0 = nonlinear)
weights	optional n x n matrix of edge weights (e.g., inverse distance)

Details

Solves: min ||W y_s - y_r||^2 + lambda_smooth * sum_(i~j) w_ij (r_i - r_j)^2 + lambda_entropy * sum(y_s * log(y_s)) s.t. y_s >= 0

Value

A list

rts2 documentation built on Jan. 21, 2026, 1:07 a.m.