similar to: using axis.Date with interaction.plot

Dear all I am trying to make an interaction plot among 6 variables; e.g. PH to be in the x axis and the rest 5 variables in the y axis. The code that I am using is the below: The name of my file is e.g. spec so > spec<-read.csv("spec.csv") >head (spec) >str(spec) >names<-names(spec)[2:6] >speclong <- reshape(spec, idvar = "id", varying =

Dear all, I want to plot 8 chemical variables in the same plot. I have used the interaction.plot command: > interaction.plot(speclong$Date,speclong$time2,speclong$outcome,xaxt="n",type="l",pch=20,xlab="", log="y", ylab="Concentration (ug/L)",trace.label="",col=rainbow(8)) However, what it gives me is dotted lines and the colours are

Dear all, I want to make a plot where I can specify the range of y axis. I am using the interaction.plot command and because the values of y axis are from 2 to 500, I am using a logarithmic scale. >interaction.plot(speclong$Date,speclong$time2,speclong$outcome,xaxt="n",type="l",pch=20,xlab="", log="y", ylab="Concentration

Dear R users, I have more of a statistical/econometric question than straight R one. I have a data set with the discrete hazard rate of small firms survival on 400 counties over a period of 9 years. This data was generated using census information from the VAT registration number of each one of these business. I would like to analyze the effect of regional factors (deprivation index, real

Hi all I am trying to generate a normal unbalanced data to estimate the coefficients of LM, LMM, GLM, and GLMM and their standard errors. Also, I am trying to estimate the variance components and their standard errors. Further, I am trying to use the likelihood ratio test to test H0: sigma^2_b = 0 (random effects variance component), and the t-test to test H0:mu=0 (intercept of the model Yij = mu

Hi, Suppose I have the following vector (data points): > x [1] 36.0 57.3 73.3 92.0 300.4 80.9 19.8 31.4 85.8 44.9 24.6 48.0 [13] 28.0 38.3 85.2 103.6 154.4 128.5 38.3 72.4 122.7 123.1 41.8 21.7 [25] 143.6 120.2 46.6 29.2 44.8 25.0 57.3 96.4 29.4 62.9 66.4 30.0 [37] 24.1 14.8 56.6 102.4 117.5 90.4 37.2 79.6 27.8 17.1 26.6 16.3 [49] 41.4 48.9 24.1

Hi, I have a few questions about glht() and the interpretation of output from Tukey's in multcomp package for lme() model. The main issue is that I noticed that a plot that I produced with code letters seem to contradict the graph itself. I provide data and code below. I end with my questions. A few things about data set. "LMA.vcp" is continuous response variable.

http://bugs.freedesktop.org/show_bug.cgi?id=15753 Summary: [Dualhead, randr12] Product: xorg Version: unspecified Platform: Other OS/Version: All Status: NEW Severity: normal Priority: medium Component: Driver/nouveau AssignedTo: nouveau at lists.freedesktop.org ReportedBy: xake at

Here is the example. > age=18:29 > height=c(76.1,77,78.1,78.2,78.8,79.7,79.9,81.1,81.2,81.8,82.8,83.5) > type=c("A", "B", "C", "D","A", "B", "C", "D","A", "B", "C", "D") >

Hi, I recently spent quite a bit of time trouble shooting a function that I had written only to discover that the problem I was having was with the comparison operator. I assumed that the following would return TRUE: > testMean <- 82.8 + 0.1 > testMean [1] 82.9 > testMean == 82.9 [1] FALSE Apparently this has to do with deciml places. Look: > newTest <- 82.0 > newTest [1]

Hi all, I am having 4 vectors like Data: num [1:4, 1:32] -82.8 -81.8 -75.5 -107.6 -87.6 ...  and I want to calculate the correlation between those. Is there a graphical way in R to plot the correlations or not? I would like to thank you in advance for your help Regards Alex [[alternative HTML version deleted]]

All, I have a data file with 56 entries that looks like this: City State JanTemp Lat Long Mobile, AL 44 31.2 88.5 Montgomery, AL 38 32.9 86.8 Phoenix, AZ 35 33.6 112.5 Little Rock, AR 31 35.4 92.8 Los Angeles, CA 47 34.3 118.7 San Francisco, CA 42 38.4 123.0 I would like to "read" this data into a dataframe. Is it possible to do without editing the datafile? D.

J?en ai profit? pour desactive VPN et autre. Du coup, je n?ai que : root at TransmitCorp~# ifconfig -a eth0: flags=4163<UP,BROADCAST,RUNNING,MULTICAST> mtu 9001 inet 172.31.6.15 netmask 255.255.240.0 broadcast 172.31.15.255 inet6 fe80::bf:52ff:fe4a:fe3c prefixlen 64 scopeid 0x20<link> ether 02:bf:52:4a:fe:3c txqueuelen 1000 (Ethernet)

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

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

Hello, I'm new to R, and I'm trying to set the number of tickmarks for a plot using xaxp, but R seems to ignore this setting completely. Maybe you've an idea what I'm doing wrong. I'm using R 1.4.1, and here's hat I'm doing: > d[,'seq'] [1] 28913 16323 13922 6237 4257 3881 4100 3781 2694 2064 1769 1550 [13] 1539 480 >

Hola. Estoy intentando crear una función pero no logro que termine de cerrar y mi manejo no permite que el google me ayude... n.reg.dep <- function(x, y) { etiqueta <- str_replace(nombres[Variable == y, Descripcion], "[ ]", "") tabla <- datos[, .N, by = .(etiqueta = A3a)] # tabla <- tabla[, Porc := round(N/sum(N)*100,1)] # % tabla[, PorcAc :=

  Hi r-users,   I would like to use gev and my data (annual rainfall ) is as follows:   > head(dat,20) A B C D E F G H I J 1 45.1 41.5 58.5 50.1 46.0 49.1 37.7 49.1 59.8 54.0 2 50.3 39.8 49.4 56.4 49.4 48.8 42.1 49.8 49.4 58.3 3 41.7 39.3 44.6 39.1 35.7 41.5 40.8 40.8 38.5 45.6 4 50.7 33.9 48.4 28.2 35.5 39.1 61.4 17.0 30.7 38.3 5 39.3 30.6 46.9 23.8 25.8

Estimado Mauricio Monsalvo R es un lenguaje medio complicado, no es orientado a objetos, aunque hay formas para un trabajo con objetos, por otro lado se puede definir una función o emplear 5 paquetes para lo mismo en dos líneas de código. Usted tiene 1500 líneas de código, no es fácil de comprenderlas, tampoco hay recetas mágicas. Yo ordenaría como si fuesen cajas, una entrada, un proceso

Hi R-users, I'm not sure what's wrong and how do I check the error? I have 3 sets of data > aug_dt1  [1]  22.8  49.6  77.9  67.6  91.2  48.9 124.6  54.6  85.8  62.8  63.3 174.7  32.3  22.7  99.9 123.2   4.8 149.0  66.0 [20]  73.9  37.4  22.4  69.5  87.3  66.9  87.2  81.5 109.1  47.4  22.8  92.4  60.9  77.5  91.3  91.9  78.2  39.4 107.5 [39]  57.9  65.5  76.0  47.2 145.5  95.9 106.0