search for: degs

r-help lattice adepts: I have a question which is somewhat geospatial, so I posted to r-sig-geo rather than here: https://stat.ethz.ch/pipermail/r-sig-geo/2012-November/016757.html > summary: How to overlay a geographical map on each panel in a lattice > (or Trellis), e.g., of levelplot's? Note I am not inquiring about > creating choropleth maps[,] which Sarkar 2008 covers quite

Dear r-help, Somewhere in my innocuous function to rotate an object in Cartesian space I've created a monster that completely locks up my computer (requires a hard reset every time). I don't know if this is useful description to anyone - the mouse still responds, but not the keyboard and not windows explorer. The script only does this when the input matrix is large, and so my initial

Hi all, Please let me know if this isn't the correct place to report bugs in contributed code. Otherwise, the following code contains one additional line and a short comment above it. The extra line of code catches the unusual situation where a data column contains all 0 values. The corrected code is below the signature. Thanks for your help. Tom Thomas S. Dye, Ph.D.

...the answer back to the correct -ve or +ve, for example, if; D<--69 M<-8 S<-10 then decimal<-D+(M/60)+(S/3600) -69+(8/60)+(10/3600) = this would equal -68.86389 (which is wrong, it should be -69.13611, so i used the following function) decimal<-(abs(D)+(M/60)+(S/3600)) decimal.degs<-sign(D)*decimal decimal.degs -69.13611 because ((69+(8/60)+(10/3600)=69.13611) and then the -sign is put back in. This works fine untill D=0 because then 'sign' does not give 0 a +ve sign it takes it as 0 and multiplies decimal by 0 to give 0. example D<-0 decimal<-D+(M/60)+(...

Hi! How to calculate the correct SE of mean in a nested or spliplot anova? Nested example: --------------------- m <- aov(Glycogen~Treatment+Error(Treatment/Rat/Liver)) > m Call: aov(formula = Glycogen ~ Treatment + Error(Treatment/Rat/Liver)) Grand Mean: 142.2222 Stratum 1: Treatment Terms: Treatment Sum of Squares 1557.556 Deg. of Freedom 2 Estimated

Why do I see this error? > library(stats) > require(stats) [1] TRUE > > tHSD <- TukeyHSD(aov) Error in TukeyHSD(aov) : no applicable method for "TukeyHSD" In case it helps: > aov Call: aov(formula = roi ~ (Cue * Hemisphere) + Error(Subject/(Cue * Hemisphere)), data = roiDataframe) Grand Mean: 8.195069 Stratum 1: Subject Terms: Residuals Sum

Hi, Assuming that you provided the sample data from the file. temp <- readLines(textConnection("#Hogd/met, Temp, 005[M], Value #Hogd/met, Difftemp, 051[M], Value BA0+ 1 MTEMP005 1 [deg.C] 2 MDTMP051 1 [deg.C] EOH 891231, 2400, -1.5, -0.21, 900101, 0100, -1.4, -0.25, 900101, 0200, -1.6, -0.28, 900101, 0300, -1.7, -0.25, 900101, 0400, -2.1, -0.0999999, 900101, 0500, -2.3, -0.0899999,

Dear colleagues, I'm trying to have a look at the Assortative and Disassortative ( http://en.wikipedia.org/wiki/Assortative_mixing) of the network I have. But it seems that the igraph hasn't mentioned that yet. I have to get the in/out degree of the vertices of each edge and calculate the Pearson's Correlation coefficient which seems to be quite a huge task for me. :( So I wonder if

Goodmorning, This is a documentation related question about the B-spline function in R. In the help file it is stated that: "df degrees of freedom; one can specify df rather than knots; bs() then chooses df-degree-1 knots at suitable quantiles of x (which will ignore missing values)." So if one were to specify a spline with 6 degrees of freedom (and no intercept) then a basis

Dear all,   I have the following written example > coords <- "51°30'48.58\"N" > > as.integer(strsplit(coords, "°")[[1]][1]) [1] 51 > as.integer(strsplit(strsplit(coords, "°")[[1]][2], "'")[[1]][1]) [1] 30 > as.numeric(strsplit(strsplit(strsplit(coords, "°")[[1]][2], "'")[[1]][2],

Dear All- I am trying to merge two data files - they have different date formats and different times zones. I need to match up the date/time of the datasets and then invoke a conditional statement, such as: if dataC$mph is >= 12 then keep dataM$co23 for the corresponding time/date stamp. snippets of data files: *dataC.txt* LST in mph Deg DegF DegF2 % volts Deg

I am trying to reproduce Figure 10.5 of Loader's book: Local Regression and Likelihood. The code provided in the book does not seem to work. I have managed (a while ago) to get the accompanied R-code for the figures in the book (file called lffigs.R) from somewhere - cannot find it on the web anymore. The code in the .R script file does not work either. Could anybody please direct me in

I am merely trying to reproduce Figure 1.2 of Chris Chatfield's 6th edition of his The Analysis of Time Series: An Introduction (page 2). The S-PLUS code is on pages 305-306. I am almost there but I am having a heck of a time trying to modify and change the x-axis per the book. The book shows the x-axis with 10 tick marks, correctly positioned, and labeled "Jan 53", ...,

Hi mailinglist members, I’m actually working on a time series prediction and my current approach is to decompose the series first into a trend, a seasonal component and a remainder. Therefore I’m using the stl() function. But I’m wondering how to get the single components in order to predict the particular fitted series’. This code snippet illustrates my problem: series <-

Apologies if this is this too obscure for R-help. In package splines, ns(x,,knots,intercept=TRUE) produces an n by K+2 matrix N, the values of K+2 basis functions for the natural splines with K (internal) knots, evaluated at x. It does this by first generating an n by K+4 matrix B of unconstrained splines, then postmultiplying B by H, a K+4 by K+2 representation of the nullspace of C (2 by K+4),

Dear memberships, I'm trying to estimate the following multivariate local regression model using the "locfit" package: BMI=m1(RCC)+m2(WCC) where (m1) and (m2) are unknown smooth functions. My problem is that once I get the regression done I cannot get the fitted values of each of this smooth functions (m1) and (m2). What I write is the following library(locfit) data(ais)

I am analyzing from a very simple experiment. I have measured plants of two different colours (yellow and purple) in 9 different populations. So, I have two different factors : a fixed effect (Colour with two levels) and a random one (Population with 9 levels). I first analyzed the data with the aov function LargS is the variable aov(formula = LargS ~ Col + Error(Col/Pop)) Terms:

Hi, This is Kotien Wu from NIH/NCI. We want to use R function for our web: http://cgap.nci.nih.gov It works for functions in R/R-1.9.1/src/nmath/standalone very well. We have function GetPvalueForT.c which has #define MATHLIB_STANDALONE 1 #include <Rmath.h> double GetPvalueForT ( double t, double deg ) { return 2 * pt(t, deg, 0, 0); } We create GetPvalueForT.i, which has /* File :

Dear R-users, One of the main reasons I moved from GAUSS to R (as an econometrician) was because of the existence of the library LOCFIT for local polynomial regression. While doing some checking between my former `GAUSS code' and my new `R code', I came to realize LOCFIT is not quite doing what I want. I wrote the following example script:

Dear all, I am attempting to convert 10 NetCDF files into a single NetCDF file, due to the data input requirements of a model I hope to use. I am using the ncdf package, version 1.6. The data are global-scale water values, on a monthly basis for 10 years (ie. 120 months of data in total; at present the data are separated by year, with 12 months of data in each file - mrunoff_1986 through to