Estimation {GDILM.ME}

Estimating parameters along with corresponding variances based on the proposed model.

Description

Estimating parameters along with corresponding variances based on the proposed model.

Usage

Estimation(
  ITER,
  MHiteration,
  eps,
  d,
  nSample,
  mm,
  time,
  MuxStar0,
  MuxInd0,
  SigmaxStar0,
  SigmaxInd0,
  Sigmav0,
  Sigmaw0,
  lambda0,
  sigma0,
  delta0,
  alpha0,
  beta10,
  beta20,
  beta30,
  beta40,
  InfPeriod,
  g
)

Arguments

ITER

The number of simulation runs

MHiteration

The number of iterations in Metropolis–Hastings algorithm

eps

Stopping value for MCECM algorithm

d

distance between cells

nSample

number of sample in each cell

mm

Number of areas.

time

Maximum time.

MuxStar0

Mean of unobserved areal level covariates.

MuxInd0

Mean of unobserved individual level covariates.

SigmaxStar0

Variance of unobserved areal level covariates.

SigmaxInd0

Variance of unobserved individual level covariates.

Sigmav0

Variance of areal level measurement error variable.

Sigmaw0

Variance of individual level measurement error variable.

lambda0

Spatial dependency parameter.

sigma0

Over dispersion parameter.

delta0

The spatial parameter.

alpha0

Initial value for intercept.

beta10

Initial value for coefficient of observed individual level covariates.

beta20

Initial value for coefficient of observed areal level covariates.

beta30

Initial value for coefficient of unobserved individual level covariates.

beta40

Initial value for coefficient of unobserved areal level covariates.

InfPeriod

The infectious period length.

g

grid dimension

Value

the result of the function

Examples

Estimation(1,5,0.05,2,4,4,20,0,0,1,1,0.3,0.3,0.5,0.5,2.5,0,1,1,1,
1,3,2)