surveillance (version 1.12.1)

simHHH: Simulates data based on the model proposed by Held et. al (2005)

Description

Simulates a multivariate time series of counts based on the Poisson/Negative Binomial model as described in Held et al. (2005).

Usage

## S3 method for class 'default':
simHHH(model=NULL, control = list(coefs = list(alpha=1, gamma = 0, delta = 0,
       lambda = 0, phi = NULL, psi = NULL, period = 52),
       neighbourhood = NULL, population = NULL, start = NULL),       length)
## S3 method for class 'ah':
simHHH(model, control = model$control, length)

Arguments

control

list with [object Object],[object Object],[object Object],[object Object]

model

Result of a model fit with algo.hhh, the estimated parameters are used to simulate data

length

number of time points to simulate

Value

• Returns a list with elements
• data
  disProgObj of simulated data
• mean
  matrix with mean $\mu_{i,t}$ that was used to simulate the data
• endemic
  matrix with only the endemic part $\nu_{i,t}$
• coefs
  list with parameters of the model

encoding

latin1

source

Held, L., H�hle{Hoehle}, M., Hofmann, M. (2005). A statistical framework for the analysis of multivariate infectious disease surveillance counts. Statistical Modelling, 5, p. 187-199.

Details

Simulates data from a Poisson or a Negative Binomial model with mean $$\mu_{it} = \lambda y_{i,t-1} + \phi \sum_{j \sim i} y_{j,t-1} + n_{it} \nu_{it}$$ where $$\log \nu_{it} = \alpha_i + \sum_{s=1}^{S}(\gamma_s sin(\omega_s t) + \delta_s cos(\omega_s t))$$ $\omega_s = 2s\pi/\code{period}$ are Fourier frequencies and $n_{it}$ are possibly standardized population sizes.