changetimeFSTP: Changes over time of the final size and turning point...

In DengueParmEst: Parameter estimates (and real-time prediction) of a single dengue outbreak

Description

This function provides the changes over time of the final size and turning point estimates for each built-in model and model averaged. The output of the function are two tables, one for final size and the other for turning point. In the row appear the different time periods since is required until the end of time point available. In the columns are the built-in model and model averaged.

Usage

## Object of the S3 class dengue
changetimeFSTP(inc, time, ini, start = NULL)

Arguments

inc,time	Vector of equal length specifying incidence (number of reported cases per time unit) and time interval (from the start of outbreak).
ini	Time point from which is required to see the changes over time of the final size and turning point estimates
start	A list with the starting values of the model to be used for fitting the data. If model="all" the imput must be a list of a list with the starting values of Richards, 3P logistic, Sigmoid Emax, Gompertz, Weibull and 5P logistic model parameters. By default, the initial values are provided by self-starting functions.

Value

An object with the changes over time of the final size and turning point estimates for each built-in model and model averaged. It is a list:

Incidence	All the available incidences
Time	All the available time points
Period	Time period required to see the changes over time of the final size and turning point estimates
FSchangetime	A Table with the changes over time of the final size for the time period required
TPchangetime	A Table with the changes over time of the turning point for the time period required
function.type	Name of the function
model.type	models used to estimate

Generic functions such as plot and summary have methods to show the results of the fit.

Author(s)

Carlos Sebrango, Lizet Sanchez, Ziv Shkedy

References

K. Burnham, D. R. Anderson, Model Selection and Multimodel Inference: A Practical Information-theoretic Approach, 2nd Edition, Springer-Verlag, New York, 2002.
G. Claeskens, N. L. Hjort, Model selection and model averaging, Cambridge University Press, 2008.

Examples

require(nlme)
require(drc)
require(NRAIA)


##Incidence Data example 1
inc1 <-c(1, 0, 2, 5, 2, 2, 3, 5, 7, 14, 17, 18, 20, 38, 50, 45,
57, 44, 12, 11, 10, 2, 3, 0, 3, 2, 2, 0, 2, 0, 0, 0, 1, 2, 2, 1)

##Incidence Data example 2
inc2<-c(5, 4, 4, 3, 7, 1, 4, 4, 9, 21,19, 33, 49, 45, 46, 28, 
25, 10, 5, 6, 2, 1, 4, 5, 0, 3, 2, 2, 1, 0, 3, 0, 2, 2)

## time vectors
tii<- c(1:36)
ti2<- c(1:34)

## (for Incidence data example 1)
## Changes over time, since time point 25 to time point 36, of the final size and turning point 
## estimates for each built-in model and model averaged

changetimeFSTP(inc1,tii,25)


## (for Incidence data example 2)
## Changes over time, since time point 19 to time point 34, of the final size and turning point 
## estimates for each built-in model and model averaged

changetimeFSTP(inc2,ti2,19)

DengueParmEst documentation built on May 2, 2019, 5:17 p.m.