Displaying 4 results from an estimated 4 matches for "semivariance".
2004 Feb 18
5
overlay points on plot
...t. Following an earlier example on the list I've created an empty plot as follows
> xlim <- range(as.numeric(c("0","10000")))
> ylim <- range(as.numeric(c("0","25")) )
> plot(NA, xlim=xlim, ylim=ylim, xlab="distance", ylab="semivariance")
However when I try to plot something on it, I get the following error:
> points(v[2],v[3])
Error in as.double.default(x) : (list) object cannot be coerced to double
A sample of my data looks like the following V[2]:
gamma
1 0.040000
2 0.582500
3 1.574545
4 7.126500
.......
2006 Aug 15
4
nls
Is there anyway to change any y[i] value (i=2,...6) to make following NLS workable?
x <- c(0,5,10,15,20,25,30)
y <- c(1.00000,0.82000,0.68000,0.64000,0.66667,0.68667,0.64000)
lm(1/y ~~ x)
nls(1/y ~~ a+b*x^c, start=list(a=1.16122,b=0.01565,c=1), trace=TRUE)
#0.0920573 : 1.16122 0.01565 1.00000
#Error in numericDeriv(form[[3]], names(ind), env) :
# Missing value or
2007 Jan 05
1
gstat package. "singular" attibute
Hello,
I'm using the gstat package within R for an automated procedure that
uses ordinary kriging.
I can see that there is a logical ("singular") atrtibute of some
adjusted model semivariograms:
.- attr(*, "singular")= logi TRUE
I cannot find documentation about the exact meaning and the implications
of this attribute, and I dont know anything about the inner calculations
2003 Aug 14
2
Using spline parameters to generate data
# I need to generate some data. I'm modeling some time series that follow
a
# negative exponential decay (mostly). I have 20 samples that can easily
be fit with cubic splines.
# What I want to do is generate many thousands of similar samples using
the parameters from the splines
# For instance one data sample looks not unlike this:
foo.curve <- 1 * exp(-0.01 * 1:500) + 0.5