Displaying 6 results from an estimated 6 matches for "bmean".
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2009 Jan 27
1
Plotmath and line breaks in long annotations for plots
...ittle
beyond the norm, is to have a series of centered lines of text
somewhere on the plot that includes various object values and symbols.
I'd like to wrap it all up in one call to text() so that it has a
common anchor. Here is an example:
a <- c(1, 10)
b <- c(1, 10)
amean <- mean(a)
bmean <- mean(b)
plot(a, b)
# Annotation with paste()
text(amean, bmean,
bquote(paste("Here are the values\nI want to write on the plot\n\n",
amean==.(amean), "\nand\n", bmean==.(bmean))))
# Annotation without paste()
text(amean, bmean,
bquote('Here are the value...
2009 Mar 31
1
Selecting Bootstrap Statistics in the boot package
Dear all,
Let's say I have the following:
# Loading the boot package
# install.packages(boot)
library(boot)
# Generating data
set.seed(123)
x <- rnorm(100)
# Bootstrap for the sample mean
bmean <- boot(x, function(x,d) mean(x[d]), R=1000)
bmean
#
#ORDINARY NONPARAMETRIC BOOTSTRAP
#
#
#Call:
#boot(data = x, statistic = function(x, d) mean(x[d]), R = 1000)
#
#
#Bootstrap Statistics :
# original bias std. error
#t1* 0.0904059 0.004641537 0.09239923
and I would like to get j...
2012 Aug 05
1
trouble with looping for effect of sampling interval increase
...ec
#log transform the power spectral density
Logfrequency <- log(frequency)
LogPSD<- log(PSD)
#fit my line to the data
Line <- lm (LogPSD ~ Logfrequency)
#store the slope of the line
Betas <- rbind (Betas, -coef(Line)[2])
#Get values on the curve shape
BSkew <- skew (Betas)
BMean <- mean (Betas)
BMedian <- median (Betas)
Q <- quantile (Betas)
#store curve shape values
IntervalLowerQ <- rbind (IntervalLowerQ , Q[2])
IntervalUpperQ <- rbind (IntervalUpperQ , Q[4])
IntervalSkew <- rbind (IntervalSkew , BSkew)
IntervalMean <- rbind (IntervalMean , BMe...
2011 Dec 05
1
Problem in while loop
Hi all,
I have the following code,
When I run the code, it never terminate this is because of the while loop i
am using. In general, if you need a loop for which you don't know in
advance how many iterations there will be, you can use the `while'
statement so here too i don't know the number how many iterations are
there. So Can some one suggest me whats going on?
I am using the
2012 Mar 27
1
Rgdal package - get information
...250
> ysign -1
> oblique.x 0
> oblique.y 0
> driver GTiff
> projection +proj=utm +zone=23 +south +datum=WGS84 +units=m +no_defs
> file
> /MOD13Q1.A2001049.h13v11.005.2007002215512.250m_16_days_EVI.tif
> apparent band summary:
> *GDType* Bmin Bmax Bmean Bsd hasNoDataValue NoDataValue
> 1 *Int16* -32768 32767 0 0 FALSE 0
> Metadata:
> AREA_OR_POINT=Point
> TIFFTAG_SOFTWARE=MODIS Reprojection Tool v4.1 March 2009
>
>
>
> *How to read the information GDType?*
>
Thanks,
julio
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2004 Apr 27
4
Problems raised to 1/3 power and NaN
...for the function for reference:
HallBoot <- function (x) {
#statisics from the original data
psd <- sqrt((sum((x-mean(x))^2)/length(x)))
pmean <- mean(x)
n <- length(x)
k <- ((sum((x-mean(x))^3)/(length(x)*psd^3)))
#the calulation of Q
Qstat <- function (x,mean){
nb = length(x)
bmean <- mean(x)
Sb <- sqrt((sum((x-mean(x))^2)/nb))
Kb <- ((sum((x-mean(x))^3)/(nb*psd^3)))
W <- (bmean-mean)/Sb
Q <- W + (Kb * W^2)/3 + (Kb^2)*(W^3)/27 + Kb/(6*nb)
}
#Bootsrap 10000 values for Q
Q <- bootstrap(x,10000,Qstat,pmean)
#Determine the quantile of Q to use
Qa <-...