similar to: creating standard curves for ELISA analysis

Hi all, does anyone know how to automatically update starting values in R? I' m fitting multiple nonlinear models and would like to know how I can update starting values without having to type them in. thank all --- On Fri, 12/26/08, r-help-request@r-project.org <r-help-request@r-project.org> wrote: From: r-help-request@r-project.org <r-help-request@r-project.org> Subject:

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

Hello, I am trying to fit my Elisa results (absorbance readings) to a standard curve. To create the standard curve model, I performed a 4-parameter logistic fit using the 'drc' package (ExpectedConc~Absorbance). This gave me the following: > FourP A 'drc' model. Call: drm(formula = Response ~ Expected, data = SC, fct = LL.4()) Coefficients: b:(Intercept) c:(Intercept)

Dear R users, A have a dataframe (matrix) with two collumns (plot, and diameter (d)). I want all diameters values for different combination of plots. For example I want all d values for all posible combination, 100C2 (all d values for plot 1 with all d values in the plot 2.......with all d values from plot 1 with all d values from plot 100, ...... with all d values from plot 99 with all d values

Hi 1Rnwb, I am a technical support for Hitachi Solutions and I saw your post regarding ELISA analysis. When I opened up your .csv file, I noticed it was a Luminex file from the Data Collector 1.7 software. My company developed a multiplex data analysis software for the Luminex platform called http://www.miraibio.com/masterplex-qt/qt-luminex-quantitative-data-analysis-software.html MasterPlex

Dear useRs, i want to split a matrix having 1116rows and 12 columns. i want to split that matrix into 36 small matrices each having 12 columns and 31 rows. The big matrix should be splitted row wise. which means that the first small matrix should copy values which are in first 31 rows and 12 columns of the big matrix. similarly 2nd small matrix should contain values from 32nd to 63rd row of the

Dear R-User, Appreciate any helps. It looks simple, but I don't have a clue. Given that I have a dataframe of tree population with three variables: sp=species , d0=initial_size grow=growth increment from initial size per year How can I calculate the future growth increment of each tree for the next 3 years. The following Rscript was written, #---------- a0 <-

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

Dear R users, I want to aggregate all *d *data from all combination of n *plots* taken by k. Thank very much! My data is like that: plot d 1 14 1 13 1 12 1 14 1 18 1 20 1 21 1 43 1 108 1 43 2 41 2 61 2 83 2 61 2 84 2 45 2 21 2 12 2 11 ... 100 10 100 12 -- --- Catalin-Constantin ROIBU Forestry engineer, PhD Forestry Faculty of Suceava

Hi, Many apologies for sending this twice. I accidentally hit the send button before I finished writing my mail. I am new to R and I hope someone can help me with my problem. I am trying to draw a side by side barplot. There is a main experiment and there are many sub experiments within the main experiment. I would like to draw a bar plot showing the number and type of sub_experiments done for

I have a set of 52 weekly values, one is the desired high lake stage for a week, and the other is the desired low lake stage for each week. It looks like this: week High Low 1 16 14.5 2 16 14.5 3 15.95 14.45 4 15.84 14.34 5 15.73 14.23 6 15.61 14.11 7 15.5 14 8 15.38 13.88 9 15.25 13.75 10 15.13 13.63 .... 52 15 13.5 I can plot out two nice curves

Hi, I've installed Samba and started up the processes; however, I do not see the Samba server in Network Neighborhood. In using the DIAGNOSIS.txt file, I cannot get past test 3: ./smbclient -U% -L localhost. The output is as follows: added interface ip=140.188.120.55 bcast=140.188.120.255 nmask=255.255.255.0 session setup failed: Call returned zero bytes (EOF) Any insight into this

I have two large datasets (156K and 2.06M records). Each row has the hour that an event happened, represented by an integer from 0 to 23. R's histogram is combining some data. Here's the command I ran to get the histogram: > histinfo <- hist(crashes$hour, right=FALSE) Here's histinfo: > histinfo $breaks ?[1] ?0 ?1 ?2 ?3 ?4 ?5 ?6 ?7 ?8 ?9 10 11 12 13 14 15 16 17 18 19 20 21

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

is there a way to use the actual index value for plotting zoo objects this is the way that the index is set up and a sample range of what I would like to plot 01/01/06 00:00:00 - 01/01/06 23:45:00 { library(zoo) # chron library(chron) fmt.chron <- function(x) { chron(sub(" .*", "", x), gsub(".* (.*)", "\\1:00", x)) }} x <- structure(c(15.57, 15.5,

Dear R users,[IF THE FORMAT OF MY EMAIL IS NOT CLEAR, I HAVE ATTACHED A TEXT FILE FOR A CLEAR VIEW] I would like to use the R output file in Fortran. my file Is exactly in the following format. ELISA/BOTTO wATER INN FROM 1900 11 1 TO 1996 12 31 1901.11. 1 447.000 1901.11. 2 445.000 1901.11. 3 445.000 1924.11. 4 445.000 1924.11. 5 449.000 1924.11. 6 442.000 1924.11. 7

HI Elisa, You could use ?cut() vec1<-c(33,18,13,47,30,10,6,21,39,25,40,29,14,16,44,1,41,4,15,20,46,32,38,5,31,12,48,27,36,24,34,2,35,11,42,9,8,7,26,22,43,17,19,28,23,3,49,37,50,45) label1<-unlist(lapply(mapply(c,lapply(seq(0,45,5),function(x) x),lapply(seq(5,50,5),function(x) x),SIMPLIFY=FALSE),function(i) paste(i[1],"<x<=",i[2],sep="")))

Dear all, ## I have 4 tables like this: satu <- array(c(5,15,20,68,29,54,84,119), dim=c(2,4), dimnames=list(c("Negative", "Positive"), c("Black", "Brown", "Red", "Blond"))) dua <- array(c(50,105,30,8,29,25,84,9), dim=c(2,4), dimnames=list(c("Negative", "Positive"),

Hi, Try this: el<- read.csv("el.csv",header=TRUE,sep="\t",stringsAsFactors=FALSE) ?elsplit<- split(el,el$st) ? datetrial<-data.frame(date1=seq.Date(as.Date("1930.1.1",format="%Y.%m.%d"),as.Date("2010.12.31",format="%Y.%m.%d"),by="day")) elsplit1<- lapply(elsplit,function(x)

Dear all, I am trying to estimate a system of equations with a Seemingly Unrelated Regression. However because of the characteristics of the data I'd like to do it with a negative binomial estimation. Would anybody know how to implement a Seemingly Unrelated Negative Binomial (SUNB) estimation in R? Thank you in advance for your help. Best regards, Elisa Lanzi -- Elisa Lanzi PhD student in