make.design: Create the design matrices

In jimhester/surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Description

Creates the design matrices needed for meanResponse

Usage

make.design(disProgObj, control=list(lambda=TRUE, neighbours=FALSE, 
   linear=FALSE, nseason=0,
   negbin=c("none", "single", "multiple"), 
   proportion=c("none", "single", "multiple"),lag.range=NULL) )

Arguments

disProgObj

object of class disProg

control

control object: lambda If TRUE an autoregressive parameter λ is included, if lambda is a vector of logicals, unit-specific parameters λ_i are included. By default, observations y_t-lag at the previous time points, i.e. lag=1, are used for the autoregression. Other lags can be used by specifying lambda as a vector of integers, see algo.hhh for details. neighbours If TRUE an autoregressive parameter for adjacent units φ is included, if neighbours is a vector of logicals, unit-specific parameters φ_i are included. By default, observations y_t-lag at the previous time points, i.e. lag=1, are used for the autoregression. Other lags can be used by specifying neighbours as a vector of integers. linear a logical (or a vector of logicals) indicating wether a linear trend β (or a linear trend β_i for each unit) is included nseason Integer number of Fourier frequencies; if nseason is a vector of integers, each unit i gets its own seasonal parameters negbin if "single" negative binomial rather than poisson is used, if "multiple" unit-specific overdispersion parameters are used. proportion see details in algo.hhh lag.range determines which observations are used to fit the model

Value

Returns a list with elements

Y	matrix with number of cases y_it in unit i at time t as elements, i.e. data without the first time point.
Ym1	matrix with previous number of cases y_i,t-1, i.e data without the last time point.
Ym1.neighbours	matrix with weighted sum of earlier counts of adjacent units sum_(j ~ i) w_ji * y_j,t-1
nOfNeighbours	vector with number of neighbours for each unit i
X.trendSeason	design matrix for linear trend and seasonal components
populationFrac	matrix with corresponding population proportions
dimTheta	list with number of parameters used in model
control	control object
disProgObj	Object of class disProg
lag	which lag is used for the autoregressive parameters λ and φ
nObs	number of observations

Author(s)

M.Paul, L. Held

jimhester/surveillance documentation built on May 19, 2019, 10:33 a.m.