search for: height

...t of variables in a dataframe pertaining to a particular pattern? This is so simple but I cannot find a straightforward answer. I want to be able to pass the contents of that list to a "for" loop. So let us assume that one has a dataframe whose name is Data. And let us assume one had the height of a group of people measured at various ages. It could be made up of vectors Data$PersonalID, Data$FirstName, Data$LastName, Data$Height.1, Data$Height.5, Data$Height.9, Data$Height.10,Data$Height.12,Data$Height.20....many many more variables. How would one create a vector of all the Height vari...

I see the new kernel available in the plus repository... is there some way to view what the differences are between that and the mainline kernel?

Hi, I'm scratching my head as to why I can't use the subset() command to remove one line of data from a data frame. There is just one row (out of 45840) that I'd like to remove and it can be identified using.... > dim(raw.all.clean) [1] 45840 10 > subset(raw.all.clean, Height.1 == 0 & Height.2 == 0) Sample.Name Well SNP Allele.1 Allele.2 Size.1 Size.2 Height.1 47068 CA0153 O02 rs2106776 NA NA 0 Height.2 Pool 47068 0 3 (Note that the row index of 47068 which is higher than the rows reported by dim()...

...intuitively, to me at least, the command x[-integer(0)] should leave x untouched. However the actual output under R2.4.0 is integer(0). A slightly more involved example demonstrates why I think this behaviour is back to front. First we define a data frame, in this case some people, with their heights. peoples.heights = data.frame(names = c("Alice", "Bob", "Carol"), heights = c(1.67, 1.85, 175)) To make sure the heights are sensible, we define a filter out impossibly tall people. dubious.records = which(peoples.heights$heights > 2.5) #3 peoples.heigh...

...windows(rescale="fixed") does not keep original device size > ## (probably device initialization error) > ############################################################################### > > dev.show <- function(){ > din <- par("din") > c(width=din[1], height=din[2], aspectratio=din[1]/din[2]) > } > width <- 42/2.54 > height <- 29.7/2.54 > > > width > [1] 16.53543 > > height > [1] 11.69291 > > width/height > [1] 1.414141 > > > > windows(width=width, height=height, rescale="R") > &g...

Sorry for the confusion, here is the edited question. The data= Stand_Height (attached) is recorded from 12/1/2009 to 12/31/2015 (25 observations) and the other dataset (leafbiom) is recorded from 10/7/2009 to 12/29/2016 (daily observations). I want to use the 25 observations of stand height to predict the daily stand height from 10/7/2009 to 12/29/2016. The daily stand he...

...mi *Ignorancia*. Estoy corriendo la siguiente instruccion, ggsave(paste('img/',plotName,'.png', sep='') y resulta el error: ggsave(paste('img/',plotName,'.png', sep='') Saving 7.32 x 4.87 in image Error in grDevices::png(..., width = width, height = height, res = dpi, : unable to start png() deviceIn addition: Warning messages:1: In grDevices::png(..., width = width, height = height, res = dpi, : unable to open file 'img/StreetRobberyKde2d.png' for writing2: In grDevices::png(..., width = width, height = height, res = dpi, :...

...########################## ## windows(rescale="fixed") does not keep original device size ## (probably device initialization error) ############################################################################### dev.show <- function(){ din <- par("din") c(width=din[1], height=din[2], aspectratio=din[1]/din[2]) } width <- 42/2.54 height <- 29.7/2.54 > width [1] 16.53543 > height [1] 11.69291 > width/height [1] 1.414141 > windows(width=width, height=height, rescale="R") > dev.show() width height aspectratio 9.229167 6.38...

...from a rectangular data array. I've been trying to play with parameters to the xmlToDataFrame function in the XML package but I dont get it to extract the data frame. Reading the file with xmlTreeParse seems to work without error. This is what the result should look like: Name Sex Age Height Weight 1 Alfred M 14 69.0 112.5 2 Alice F 13 56.5 84.0 3 Barbara F 13 65.3 98.0 4 Carol F 14 62.8 102.5 5 Henry M 14 63.5 102.5 6 James M 12 57.3 83.0 7 Jane F 12 59.8 84.5 8 Janet F 15 62.5 112.5 9 Jeffrey M 13 62.5...

Hello, In the following I tried 3 versions of an example in R help. Only the two first predict command work. After : library(splines) require(stats) 1) fm1 <- lm(weight ~ bs(height, df = 5), data = women) ht1 <- seq(57, 73, len = 200) ph1 <- predict(fm1, data.frame(height=ht1)) # OK plot(women, xlab = "Height (in)", ylab = "Weight (lb)") lines(ht1, ph1) 2) height <- women$height # 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 weight <...

Hi folks, I have 25 stand height observations over 7 years period and daily leafbiomass data during this period. I want to use the 25 plant height observations as inputs and predict the daily stand height during the 7 years. SH=matrix(data=NA , nrow = 2641, ncol = 1) for (i in 1:2641) { SH<- predict(lm(height~Date, data=Sta...

hi everyone, wondering if you could help me with a novice problem. I have a data frame called subjects with a height and weight variable and want to calculate a bmi variable from the two. i have tried: attach(subjects) bmi <- (weight)/((height/100)^2) but it comes up with the error: Warning messages: 1: In Ops.factor(height, 100) : / not meaningful for factors 2: In Ops.factor((weight), ((height/100)^2)) :...

...uint8 *data; if (image->jpegtables) { ret = swfdec_jpeg_decode_argb ( image->jpegtables->data, image->jpegtables->length, image->raw_data->data, image->raw_data->length, - (void *)&image->data, &image->width, &image->height); + (void *) &data, &image->width, &image->height); } else { ret = swfdec_jpeg_decode_argb ( image->raw_data->data, image->raw_data->length, NULL, 0, - (void *)&image->data, &image->width, &image->height); +...

I have a sample of lung capacities from a population measured against height. I need to know the 95% CI of the lung capacity of a person of average height. I have fitted a regression line. How do I get a minimum and maximum values of the 95% CI? My thinking was that this has something to do with covariance, but how? My other thinking was that I could derive the 0.975...

..., xlab="", axes = FALSE, aspect = asp.ratio.3, ylab="", main='', sub="", colorkey = FALSE, region = TRUE, scales = list(draw = FALSE)) # so the three basic types of plot I will have toy.vp <- viewport(width = .8, height = .8, just = 'centre', name = 'toy') # this is for my levelplot X11() pushViewport(toy.vp) grid.rect(gp = gpar(col = 'grey')) print(test.1, newpage = FALSE) X11() pushViewport(toy.vp) grid.rect(gp = gpar(col = 'grey')) print(test.2, newpage...

Once again, you are over-writing your variable. This time, you are overwriting the entirety of Stand_Height with the timeseries of height. Perhaps you should spend some time with one of the good introductory R resources out there, and think a bit more about your procedure. Sarah On Fri, Jun 30, 2017 at 11:23 AM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: > Sorry for the confusion, here is...

...ges. - You're never predicting from your linear model using the other data not in the regression. - Leaf biomass data is never used for anything. I would have thought that you would use leaf biomass as the predictor variable, not Date. - I'm not sure why you want the cumulative sum of stand height; that doesn't make sense to me. I'm guessing you want: height.model <- lm(height ~ leafbiomass, data = Stand_Height) pred.height <- predict(height.model, leafbiom) # not sure about the reasoning behind this SH <- cumsum(pred.height) You don't need a loop. Overwriting SH is...

A secure macro It’s like static but well optimized. Any ideas how I can implement it universally? I thought about a secure application to help with compiling and security. It’s like sudo but more secure and can chain. I don’t know much about pipes and streams, but I’m pretty sure I can write it into llvm with enough time and help. Another thing, and I got trolled off gcc’s mailing list for this,

...1 under windows. In a barplot, I want to mark one of the bars with a special border color. For example: barplot(c(3, 7, 11), border = c(NA, "red", NA)) But how to do this when the bars are stacked? for example: barplot(matrix(1:6, ncol=3)) # border of second bar (i.e. the one with total height = 7) should be red again, I try: barplot(matrix(1:6, ncol=3), border = c(NA, "red", NA)) Obviously, this doesn't give me what I want. Your advice would be appreciated; kind regards Heinrich.

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