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Last data update: 2014.03.03

R: Spatio-Temporal Kernel Density Estimation with Density...

stkde

R Documentation

Spatio-Temporal Kernel Density Estimation with Density Contours

Description

stkde calculates the three dimensional kernel density estimation of spatio-temporal mixed data,continous space and discrete time.

Usage

stkde(xlong,ylat,ztime,xgrids,ygrids,breaks,alpha,nrowspar,...)

Arguments

`xlong`	Projected planar coordinates of longitude.
`ylat`	Projected planar coordinates of latitude.
`ztime`	The integer variable,such as YEAR,1990,1991 or 1,2.
`xgrids`	Number of grids to evaluate the density in the x direction.
`ygrids`	Number of grids to evaluate the density in the y direction.
`breaks`	`breaks` is to be used to specify the interval size for a numeric vector of probabilities with values in [0,1]. Defaults to the 0.05.
`alpha`	Specify the density level for indicating the statistically significant regions. Its default value is 0.05.
`nrowspar`	specify the number of rows when plotting the figures in a panel. The default number is 1.
`...`	additional arguments supplied to control various aspects of `stkde`.These arguments are the same as `npudensbw` in the np package, see details there.

Details

stkde is a method to conduct the spatio-temporal kernel density estimation, when the time variable is discrete or categorial variable,not continuous variable.

Value

stkde returns a stkde object, with the following components:
bw: bandwidth(s), scale factor(s) or nearest neighbours for the data.
dens: kernel estimation of the density (cumulative distribution) at the evaluation points.

Note

If you are using data of mixed types, then it is advisable to use the data.frame function to construct your input data and not cbind, since cbind will typically not work as intended on mixed data types and will coerce the data to the same type.

Author(s)

Zhijie Zhang, epistat@gmail.com

References

Li, Q. and Racine, J.S.Nonparametric Econometrics: Theory and Practice, Princeton University Press. 2007.
Hayield, T. and Racine,J.S. “Nonparametric Econometrics: The np Package,”.Journal of Statistical Software,2008,27(5):http://www.jstatsoft.org/v27/i05/.

Examples

## Not run: 
#Example1-uneven number of years
#Dataset1
# We will generate a 3 different stages' case points.
# The higher density are in the off-diagonal direction.
x1<-c(runif(100,0,1),runif(50,0.67,1))
y1<-c(runif(100,0,1),runif(50,0.67,1))
d1<-data.frame(x1,y1)
colnames(d1)<-c("x","y")
x2<-c(runif(100,0,1),runif(50,0.33,0.67))
y2<-c(runif(100,0,1),runif(50,0.33,0.67))
d2<-data.frame(x2,y2)
colnames(d2)<-c("x","y")
x3<-c(runif(100,0,1),runif(50,0,0.33))
y3<-c(runif(100,0,1),runif(50,0,0.33))
d3<-data.frame(x3,y3)
colnames(d3)<-c("x","y")
d<-rbind(d1,d2,d3)
d$tf<-c(rep(1,150),rep(2,150),rep(3,150))
#d is the simulated data
#d[1,]
#plot(d1);points(d2,col="red");points(d3,col="green")
#Key Code
#attach(d)
samkde<-stkde(xlong=d$x,ylat=d$y,ztime=d$tf,xgrids=20,ygrids=20,
        breaks=0.05,alpha=0.05,nrowspar=1,bwmethod="cv.ml")
samkde$bw
samkde$dens
#Example2-even number of years
#Dataset2
x12<-c(runif(100,0,1),runif(50,0.67,1))
y12<-c(runif(100,0,1),runif(50,0.67,1))
d12<-data.frame(x12,y12)
colnames(d12)<-c("x","y")
x22<-c(runif(100,0,1),runif(50,0.33,0.67))
y22<-c(runif(100,0,1),runif(50,0.33,0.67))
d22<-data.frame(x22,y22)
colnames(d22)<-c("x","y")
d2<-rbind(d12,d22)
d2$tf<-c(rep(1,150),rep(2,150))
colnames(d2)<-c("xlong","ylat","ztime")
#Running the function
samkde2<-stkde(d[,1],d[,2],d[,3],xgrids=20,ygrids=20,breaks=0.05,
         alpha=0.05,nrowspar=1,bwmethod="cv.ml")
samkde2$bw
samkde2$dens         

## End(Not run)