NaiveEstimation_RealData {GDILM.ME}

Estimating parameters along with corresponding variances based on Naive model with real data.

Description

Estimating parameters along with corresponding variances based on Naive model with real data.

Usage

NaiveEstimation_RealData(
  ITER,
  MHiteration,
  eps,
  mm,
  time,
  MuxStar0,
  MuxInd0,
  SigmaxStar0,
  SigmaxInd0,
  Sigmav0,
  Sigmaw0,
  lambda0,
  sigma0,
  delta0,
  alpha0,
  beta10,
  beta20,
  beta30,
  beta40,
  InfPeriod,
  Di,
  D,
  Nlabel,
  n,
  cov1,
  cov2,
  ww,
  vv,
  tau
)

Arguments

ITER

The number of simulation runs

MHiteration

The number of iterations in Metropolis–Hastings algorithm

eps

Stopping value for MCECM algorithm

mm

Number of areas.

time

Maximum time.

MuxStar0

Mean vector of unobserved areal level covariates.

MuxInd0

Mean vector 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.

Di

Euclidean distance between individuals

D

Neibourhood structure

Nlabel

Label for each sample from the area

n

Total number of individuals

cov1

observed individual level covariates

cov2

observed areal level covariates

ww

Unobserved individual level covariates

vv

unobserved areal level covariates

tau

tau

Value

The results of the function

Examples

NaiveEstimation_RealData(1,5,0.05,4,20,0.1,0.1,0.15,0.8,0.6,0.6,
0.85,1.1,2.7,0,1,0,1,1,3,
matrix(runif(900,min = 4,max = 20),nrow=30, byrow = TRUE),
matrix(c(2,-1,-1,0,-1,2,0,-1,-1,0,2,-1,0,-1,-1,2),nrow=4,byrow=TRUE),
rep(1:4,c(7,6,8,9)),30,runif(30, 0, 1),
runif(4,0,1),runif(30,-2,2),runif(4,0,1),
sample(c(0,1),replace = TRUE, size = 30))