similar to: Animal Morphology: Deriving Classification Equation with Linear Discriminat Analysis (lda)

R-help, I have a character vector whose elements are the names of matrixes. Something like this: > test <- ls(pattern="Oki") [1] "aaOki" "aOki" "bOki" "c1Oki" "c2Oki" "c3Oki" "cOki" "dOki" "eOki" "fOki" "gprsOki" "hOki"

Dear All, I created a script to calculate averages - two groups: "parcel" and "date" - and, based on these averages, make a graph. The problem is that 'R' does not recognize the first column even if I try to insert one. A brief example Raw data: Data <- sample(1:100, 30, replace = FALSE, prob = NULL) Date <-

Hi Everyone, I have a dataset like this mean sd 0% 25% 50% 75% 100% n BODY TEMPERATURE 36.41099 0.4015699 35.1 36.22222 36.5 36.66667 37.1 89 DIASTOLIC BLOOD PRESSURE 73.60079 9.4656186 50.0 67.00000 73.0 80.00000 95.0 253 HEIGHT 171.94000 9.2011670 153.5 166.50000 173.0 176.25000 190.0

Hi! I''ve just started playing around with the ym4r-plugin and try to update a map as explained in the README-example... but nothing happens. I can update normal html. Heres my baby-code: class AdminController < ApplicationController def index @map = GMap.new("map_div") @map.control_init(:large_map => true) @map.center_zoom_init([59.91106, 10.72223],16)

Hi R-users: [R 2.2 on OSX 10.4.3] I have a (sparse) vegetation data frame with 500 rows (sampling units) and 177 columns (plant species) where the data represent % cover. I need to summarize the cover data by returning the names of the most dominant and the second most dominant species per plot. I reduced the data frame to omit cover below 5%; this is what it looks like stacked. I have

Hi all, I was conducting a meta-analysis of single proportions(i.e. without a control group) using the metafor package. When I performed a classic fail-safe N, I noticed that the result (the number of missing studies that would bring p-value to the alpha, to be exact)was different than that I got in Comprehensive Meta-Analysis Version 2.0. I wonder why R and CMA got different results. *Below is

I would suggest to post this to the (recently created) R-sig-meta-analysis mailing list. See: https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis Best, Wolfgang >-----Original Message----- >From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Naike Wang >Sent: Monday, June 26, 2017 08:32 >To: R-help at r-project.org >Subject: [R] Classic fail-safe N >

Hello, I have a data.frame with the following format: > head(clin2) Study Subject Type Obs Cycle Day Date Time 1 A001101 10108 ALB 44.00000 98 1 2004-03-11 14:26 2 A001101 10108 ALP 95.00000 98 1 2004-03-11 14:26 3 A001101 10108 ALT 61.00000 98 1 2004-03-11 14:26 5 A001101 10108 AST 33.00000 98 1 2004-03-11 14:26 I want to transform this

Hi all, I was conducting a meta-analysis of single proportions(i.e. without a control group) using the metafor package. When I performed a classic fail-safe N, I noticed that the result (the number of missing studies that would bring p-value to the alpha, to be exact)was different than that I got in Comprehensive Meta-Analysis Version 2.0. I wonder why R and CMA got different results. *Below is

Dear list, I have following data set, which I want to plot the "Scale" variable on the x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The Mean value of each Ageclass for each sex would be connected by a line. Totally, there should be 6 lines, from which three present the Mean values of each Ageclass for respective sex. Are there any easy ways to do

I'll try to be more clear, but will have to give much more info. Here we go.... As part of my Masters in Public Health I writing a dissertation reviewing the mortality trend of internally displaced persons in camp settings in Sub Saharan Africa. I have 50 surveys with - crude mortality rate (cmr), CMR lower confidence interval(cmrlci), CMR upper confidence interval(cmruci), - recall period

Should I be able to use axis() on a barplot? i have a data.frame, the first 3 values of which are: > c[1:3,] median mean A1 56.5 58.50000 A61 73.0 73.00000 A62 63.0 63.00000 > str(c) `data.frame': 19 obs. of 2 variables: $ median: num 56.5 73 63 161 51 55 44.5 22 54 49 ... $ mean : num 58.5 73.0 63.0 161.0 47.5 ... if I do barplot(median) and then try

Hey all, here is a less hacky version of the query string C extension I posted before. http://s3.amazonaws.com/four.livejournal/20070927/qsp.tar.bz2 It uses an http11-like interface to the state machine. the escape/unescape functions are also slightly more libraryish. again, here is the about benchmark results. it seems to be about 10 times faster than the ruby functions. i''ve seen

Hi I want to create a TimeSeries object with already defined dates (in the first vector) so that all the data are coerced as a time series object with the dates as they are. Is there anyone that have an idea what to do? 2010-07-07 3.900833 3.176667 2.754167 2.045833 1.820833 2010-04-21 4.256667 3.356667 2.700000 1.820000 1.576667 2010-02-17 4.322500 3.450000 2.670000 1.792500 1.492500

Hi, Using the following simple character vector representing a time series with fractional seconds: datetime <- c("20/09/2011 13:00:59.00", "20/09/2011 13:00:59.02", "20/09/2011 13:00:59.04") Conversion to POSIXct runs into problems; the second element is not interpreted correctly: ---<--------------------cut

I have a time series for two variables measured simultaneously, but at different intervals. The variables are not independent, so the patterns in the times series are very similar (one variable goes up when the other goes up, etc). For example, let's pretend my data look something like this (but with more noise)... var1_times<-c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) var1_values<-c(0,

Dear all, I am pretty new to R only having an introduction course, so please bare with me. I am doing my PhD at The Max Planck Institute of Immunobiology where I am analyzing some calorimetry data from some mice. I have a spreadsheet consisting of measurements of the respiratory exchange rate at different time points measured every 9 minutes over some days. My goal is "bin"/average the

I am looking for help to analyze an unbalanced AB/BA cross-over design by requesting the type III SS ! # Example 3.1 from S. Senn (1993). Cross-over Trials in Clinical Research outcome<-c(310,310,370,410,250,380,330,270,260,300,390,210,350,365,370,310,380,290,260,90,385,400,410,320,340,220) subject<-as.factor(c(1,4,6,7,10,11,14,1,4,6,7,10,11,14,2,3,5,9,12,13,2,3,5,9,12,13))

Hi, I am new in R and I have problem with reading this data file 0 TITLE Title 0 XLEGEND Legend -1 LABEL x 1 1 12 1 2 30 1 3 34 I want to read only lines starting with 1 (it indicates 1st plotting line) and create data set from second and third value on this row. Thank for advice Jakub Zlamal -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list

Dear R-helpers, I want to make a series of boxplots on several numeric univariates with two group variables (species and population, population nested in species, and with population as the X-axis). In order to get a proper order of the individual populations in X-axis, I need to assign a wanted order to the factor (population). I used the levels() function to do this assignment, but it seemed