similar to: Storing output in an array or matrix

I think qqline does not do exactly what it is advertised to do ("`qqline' adds a line to a normal quantile-quantile plot which passes through the first and third quartiles."). Consider the graph: tmp <- qnorm(ppoints(10)) qqnorm(tmp) qqline(tmp) The line (which I expected go through all the points), has a slightly shallower slope than does the points plotted by qqnorm. I think

Hi, I have a simple question about quartiles in R, especially how they are calculated using the boxplot. Quartiles (.25 and .75) in boxplot are different from the summary function and also don't match with the 9 types in the quantile function. See attachment for details. Can you give me the details on how the boxplot function does calculate these values? Cheers, Rene Brinkhuis

Why am I getting a wrong result for quartiles? here is my code: > cbiomass = c(910, 1058, 929, 1103, 1056, 1022, 1255, 1121, 1111, 1192, > 1074, 1415) > summary(cbiomass) > IQR(cbiomass) The result R gives me is: For the summary > Min. 1st Qu. Median Mean 3rd Qu. Max. 910 1048 1088 1104 1139 1415 For IQR > 91.25 ********* The true Q1 is 1039

Hello, I'm currently using a simple plot to visualize some mean values. I'm having ~200 datapoints on the x-axis, each has 10 records. I'm currently plotting only the mean value of each of the datapoints. What I need is a way to visualize the quartiles/error/whatever of these points. I thought about boxplots, but I have to many points on the xaxis - it would be impossible to see

I'm trying to devide x into tertiles, but ends up with integer limits even x holds one decimal. The analysis is extremely sensitive to the limits and I like to keep them right. How can that be done? quartiles <- quantcut( x[x >= 0], q=seq(0,1, by=(1/3)) > table(quartiles) quartiles [180,344] (344,448] (448,644] 16467 16476 16452 [[alternative HTML version deleted]]

Dear all, The incredibly useful Hmisc package provides a method to generate summary tables that can be typeset in latex. The Alzola and Harrell book "An introduction to S and the Hmisc and Design libraries" provides an example that generates mean and quartiles for continuous variables, and numbers and percentages for count variables: summary() with method = 'reverse'. I

When data contains both factor and numeric variables, how to get quartiles for all numeric variables? n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <- factor(sample(c('a','b','c'),n,replace=TRUE)) x6 <- factor(1*(x5=='a' | x5=='c')) data1 <- cbind(x1,x2,x3,x4,x5,x6) data

Dear R community, I'm trying to develop a fast way of summing specific rows of a large data frame. Here is an example of the kind of data frames I'm dealing with: > refls H K L M/ISYM BATCH I SIGI 43247 1 0 5 21 79 61.44117 2.20553 1040 1 0 5 257 6 15.16316 0.54431 2324 1 0 5 257 5 46.76152 1.67858 31515 1 0 5 259 60 57.97305

For boxplot(), is it possible to pass in a parameter to change the default way that the 1st and 3rd quartiles are computed? (specifically, I'd like to use type 6 described in the quantile function). Also, what are the options for how outliers are computed, and how can one change them? Thank you [[alternative HTML version deleted]]

Hi I need some help getting results from multiple linear models into a dataframe. Let me explain the problem. I have a dataframe with ejection fraction results measured over a number of quartiles and grouped by base_study. My dataframe (800 different base_studies) looks like > afvtprelvefs basestudy quartile ef ef_std entropy CBP0908020 1 21.6 0.53 3.27

Another naive stats question. I'm trying to better understand what boxplots are telling me. I think what I see is the median and the boundaries of the 1st and 3rd quartiles. The whiskers represent the range of the data unless there are points which are outside "range" (default: 1.5) times the distance from the median to that quartile. Is that right? I've read the

I'll appreciate if some one can help me with the following loop. This is the logic of the loop, if we have the following data; > x.df x.dif . . . . 102 0.00 103 0.42 104 0.08 105 0.00 106 0.00 107 0.00 108 -0.16 109 -0.34 110 0.00 111 -0.17 112 -0.33 113 0.00 114 0.00 115 0.00 116 0.33 117 0.17 118 0.00 . . . . I'm trying to find i's where for (i

Dear mailing group, This is my first time here. Glad to have this resource! I am currently trying to load an Excel file into R (limma package loaded) using the source(*name of directory*) command, but it cannot open the file. I renamed the file as .R and .RData, to no avail. The Excel data contains one gene name per row and about 100 data points per gene (columns). I am only used to

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Hi all, I''ve got a simple contingency table produced with table(), and the upper and lower quartiles (quantile25 and quantile75) for the same dataset. Is there a function that tells me in which category does the value of the quartile falls into? for example: tabsp <- table(fam$I[fam$I>0]) 1 3 6 6 1 1 and for the cumulative frequency distribution tabcum <- cumsum(tabsp) 1 3

Oftentimes I want to make outputs to be displayed on the R console. However, after I execute a program with a sink command in it the R console becomes unresponsive. Meaning that the following occurs in R console: > source("Program_containing_sink.R") > a<-1 > a > >sink() >a > R help says that sink() will bring output back to the console but i's not

I really like the ease of use with the boxplot command in R. I would rather have a boxplot that shows the average value and the standard deviation then the median value and the quartiles. Is there a way to do this? Chad Junkermeier, Graduate Student Dept. of Physics West Virginia University PO Box 6315 210 Hodges Hall Morgantown WV 26506-6315 phone: (304) 293-3442 ext. 1430 fax: (304)

I am very new to R so forgive me if this seems basic but I have done extensive searching and failed to come up with the answer for myself. I am trying to label a boxplot I have created with the values for the median, upper and lower quartiles and max and min values. I have been unable to do this or find anything on the net to say how it might be done. Is this possible and if so how? Regards,

Hi I'm trying to extract complete rows from a dataframe by group based on the maximum in a column within that group. Thus I have a dataframe: cvd_basestudy ... es_time ... _____________ study1 ... 0.3091667 study2 ... 0.3091667 study2 ... 0.2625000 study3 ... 0.3033333 study3 ... 0.2625000 __________ etc I can extract the basestudy and the max(es_time)

Hi everyone, I'm a new R user (if this is a really basic question, please do excuse me...) and I'm having some questions regarding a deciles problem. I have a variable which I need to categorize according to its deciles (X). However, this categorization should be made into another variable (call it NewVar). Ex. for the quartiles case (just for the sake of exposition, since I need