Re: [R] mixture univariate distributions fit
Hallo Bert Sorry for the confusion, I may not have used correct wording in describing what I wanted to do. Consider this example # 2 different distribution densities mixed together in 1:2 proportion x <- (0:100)/100 y1 <- dnorm((x, mean=.3, sd=.1) y2 <- dnorm((x, mean=.7, sd=.1) ymix <- ((y1+2*y2)/max(y1+2*y2)) plot((x, ymix) # sampling x based on mixed distribution density dist <- sample((x, size=1, replace=TRUE, prob=ymix) library(mixtools) fit <- normalmixEM(dist) summary(fit) summary of normalmixEM object: comp 1comp 2 lambda 0.334926 0.6650742 mu 0.304862 0.7036926 sigma 0.098673 0.0994382 loglik at estimate: 30935.34 I can get estimation of mu and sigma together with proportion of each (lambda) distribution in mixture. My question is if there is some package or function which could get those values ***directly from x and ymix values***, which is basically what is measured in my case. I know I could code some optimisation procedure and adopt what was done in Python https://chrisostrouchov.com/post/peak_fit_xrd_python/ for peak fitting or this one https://stats.stackexchange.com/questions/92748/multi-peak-gaussian-fit-in-r but I do not like to reinvent the wheel. I went through Chemometrics and Computational Physics task view, which I consider most appropriate to have such functions but it is usually quite specific, especially in required input data form. Anyway, thanks for your effort. I wish you best for new year 2022. Petr > -Original Message- > From: Bert Gunter > Sent: Thursday, December 30, 2021 5:10 PM > To: PIKAL Petr > Cc: r-help mailing list > Subject: Re: [R] mixture univariate distributions fit > > Petr: > > 1. I now am somewhat confused by your goals. Any curve fitting procedure > can fit curves to data, including discrete points on a smooth curve. What > cannot be done is to recover the exact parameters of the smooth curve from > which your data derive, at least not without knowing how the curve was > fitted to that underlying (particle size) data, i.e. the nature of the > parameterization (if even there was one > -- it may just be some sort of empirical smoother like kernel density > estimation or some such). > > 2. mixtools uses EM, so the similarity you noted is probably not surprising. > > 3. Given my evident confusion, I hope that this email may prompt someone > more knowledgeable than I to correct or clarify my "advice." > You may wish to further clarify what you wish to do with the parameters that > you hope to get to encourage such comments. For example, do you wish to > compare the densities you get via their parameterizations? If so, others may > be able to offer better strategies to do this, perhaps on SO -- > https://stats.stackexchange.com/ -- rather than here. > > Cheers, > Bert Gunter > > On Thu, Dec 30, 2021 at 12:36 AM PIKAL Petr > wrote: > > > > Thank you Bert > > > > The values are results from particle size measurement by sedimentation > > and they are really available only as these cumulative or density > distributions. > > What I thought about was that there is some package which could fit > > data of such curves and deliver parameters of fitted curves. > > > > Something like > > https://chrisostrouchov.com/post/peak_fit_xrd_python/ > > > > I found package EMpeaksR which results close to values estimated from > > mixtools package. > > > > test <- spect_em_gmm(temp1$velik, temp1$proc, mu=c(170, 220), > > mix_ratio=c(1,1), sigma=c(5,5), maxit=2000, conv.cri=1e-8) > > print(cbind(test$mu, test$sigma, test$mix_ratio)) > > [,1] [,2] [,3] > > [1,] 170.7744 7.200109 0.5759867 > > [2,] 229.1815 10.831626 0.4240133 > > > > But it is probably in stage of intensive development as it is limited > > in data visualisation > > > > Any further hint is appreciated. > > > > Regards > > Petr > > > > > -Original Message- > > > From: Bert Gunter > > > Sent: Wednesday, December 29, 2021 5:01 PM > > > To: PIKAL Petr > > > Cc: r-help mailing list > > > Subject: Re: [R] mixture univariate distributions fit > > > > > > No. > > > > > > However, if the object returned is the "Value" structure of whatever > > > density function you use, it probably contains the original data. > > > You need to check the docs to see. But this does not appear to be your > situation. > > > > > > Bert Gunter > > > > > > "The trouble with having an open mind is that people keep coming > > > along and sticking things into it." > > > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > > > > On Wed, Dec 29, 2021 at 3:05 AM PIKAL Petr > > > wrote: > > > > > > > > Dear all > > > > > > > > I have data which are either density distribution estimate or > > > > cummulative density distribution estimate (temp1, temp2 below). I > > > > would like to get values (mu, sd) for underlaying original data > > > > but they are > > > not available. > > > > > > > > I found mixtools package which calculate what I need but it > >
Re: [R] question about error message: "Aesthetics must be either length 1 or the same as the data (226): y and colour"
Thank you all of your help. I'm new in R. I'll follow Bert's and your
suggestions to post the question in another area in future.
Happy New Year
Kai
On Thursday, December 30, 2021, 02:05:12 PM PST, CALUM POLWART
wrote:
You will get shot down in flames for posting this here. This list is for
base-R and your query is tidyverse related so belongs on somewhere tidy
specific...
But...
mpg[[y]]
Is returning the column mpg[[y]] unfiltered but displ is filtered.
It would be possible to use mpg[[y]][ mpg$hwy<35]
But I suspect there is a better solution involving . As a data source or
perhaps select to pick only the data you want...
On 30 Dec 2021 18:42, Kai Yang via R-help wrote:
Hi R team,
I can create a plot using the code below:
library(ggplot2)
library(dplyr)
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = hwy, color = cyl)) +
geom_point()
ggsave("c:/temp/hwy_cyl.jpg",width = 9, height = 6, dpi = 1200, units = "in")
I want to do the exactly same work using function. Below is the function I
created:
plot1 <- function(y, c, f){
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = mpg[[y]], color = mpg[[c]] )) +
geom_point()
ggsave(paste0("c:/temp/", f ,".jpg"), width = 9, height = 6, dpi =
1200, units = "in")
}
plot1("hwy","cyl","hwy_cyl_f")
But I got error message when I run the code: "Aesthetics must be either length
1 or the same as the data (226): y and colour" . I checked online about the
message. My understanding is: I need to add "fill" in geom_point() statement.
My questions are:
1. is it possible to make the code work without add 'fill' in geom_point()
statement, but keep the color as same as the first code?
2. if I must add 'fill' option in geom_point() statement, how to add them in?
Should I add 266 colors name after 'fill'?
3. this is my first function in R, I'm sure there are many problems in the
code. please point out my error in the code.
Thank you,
Kai
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] question about error message: "Aesthetics must be either length 1 or the same as the data (226): y and colour"
Hello,
This seems like a repetition of a question you already asked and it has
nothing to do with the fill aesthetic.
The error message is caused by the maps
y = mpg[[y]]
color = mpg[[c]]
First you filter the data keeping only a subset of the rows but now you
are using the full data. This causes the error, the sizes of the
filtered data and of the full data are not the same.
mpg %>% filter(hwy < 35) %>% dim()
#[1] 226 11
y <- "hwy"
length(mpg[[y]])
#[1] 234
If you pass a string as variable, you must ?get the variable value, like
in the first function below, plot1.
plot1 <- function(y, c, f){
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = get(y), color = get(c))) +
geom_point()
ggsave(paste0("~/tmp/", f ,".jpg"), width = 9, height = 6, dpi =
1200, units = "in")
}
plot1("hwy","cyl","hwy_cyl_f")
Or you can use aes_string. But since the x axis is fixed, not variable,
pay attention to not mix a variable (displ) with variables' names (hwy
and cyl). So in the next function I use aes() in the initial call to
ggplot and aes_string in the geom_point layer.
plot2 <- function(y, c, f){
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ)) +
geom_point(aes_string(y = y, color = c))
ggsave(paste0("~/tmp/", f ,".jpg"), width = 9, height = 6, dpi =
1200, units = "in")
}
plot2("hwy","cyl","hwy_cyl_f2")
Hope this helps,
Rui Barradas
Às 18:42 de 30/12/21, Kai Yang via R-help escreveu:
Hi R team,
I can create a plot using the code below:
library(ggplot2)
library(dplyr)
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = hwy, color = cyl)) +
geom_point()
ggsave("c:/temp/hwy_cyl.jpg",width = 9, height = 6, dpi = 1200, units = "in")
I want to do the exactly same work using function. Below is the function I
created:
plot1 <- function(y, c, f){
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = mpg[[y]], color = mpg[[c]] )) +
geom_point()
ggsave(paste0("c:/temp/", f ,".jpg"), width = 9, height = 6, dpi = 1200, units
= "in")
}
plot1("hwy","cyl","hwy_cyl_f")
But I got error message when I run the code: "Aesthetics must be either length 1 or the same
as the data (226): y and colour" . I checked online about the message. My understanding is: I
need to add "fill" in geom_point() statement. My questions are:
1. is it possible to make the code work without add 'fill' in geom_point()
statement, but keep the color as same as the first code?
2. if I must add 'fill' option in geom_point() statement, how to add them in?
Should I add 266 colors name after 'fill'?
3. this is my first function in R, I'm sure there are many problems in the
code. please point out my error in the code.
Thank you,
Kai
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] question about error message: "Aesthetics must be either length 1 or the same as the data (226): y and colour"
1. Please read and follow the Posting Guide linked below. Among other
things, it says:
"For questions about functions in standard packages distributed with R
(see the FAQ Add-on packages in R), ask questions on R-help."
[The link is:
https://cran.r-project.org/doc/FAQ/R-FAQ.html#Add-on-packages-in-R
This gives the list of current _standard_ packages]
"If the question relates to a contributed package [ggplot is such a
package] , e.g., one downloaded from CRAN, try contacting the package
maintainer first. You can also use find("functionname") and
packageDescription("packagename") to find this information. Only send
such questions to R-help or R-devel if you get no reply or need
further assistance. This applies to both requests for help and to bug
reports."
Note that RStudio maintains its own help resources at:
https://community.rstudio.com/
This is where questions about the TidyVerse, ggplot, etc. should be posted.
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Thu, Dec 30, 2021 at 10:43 AM Kai Yang via R-help
wrote:
>
> Hi R team,
> I can create a plot using the code below:
> library(ggplot2)
> library(dplyr)
> mpg %>%
> filter(hwy <35) %>%
> ggplot(aes(x = displ, y = hwy, color = cyl)) +
> geom_point()
> ggsave("c:/temp/hwy_cyl.jpg",width = 9, height = 6, dpi = 1200, units = "in")
>
>
> I want to do the exactly same work using function. Below is the function I
> created:
> plot1 <- function(y, c, f){
> mpg %>%
> filter(hwy <35) %>%
> ggplot(aes(x = displ, y = mpg[[y]], color = mpg[[c]] )) +
> geom_point()
> ggsave(paste0("c:/temp/", f ,".jpg"), width = 9, height = 6, dpi =
> 1200, units = "in")
> }
> plot1("hwy","cyl","hwy_cyl_f")
>
> But I got error message when I run the code: "Aesthetics must be either
> length 1 or the same as the data (226): y and colour" . I checked online
> about the message. My understanding is: I need to add "fill" in geom_point()
> statement. My questions are:
> 1. is it possible to make the code work without add 'fill' in geom_point()
> statement, but keep the color as same as the first code?
> 2. if I must add 'fill' option in geom_point() statement, how to add them in?
> Should I add 266 colors name after 'fill'?
> 3. this is my first function in R, I'm sure there are many problems in the
> code. please point out my error in the code.
>
>
> Thank you,
> Kai
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] question about error message: "Aesthetics must be either length 1 or the same as the data (226): y and colour"
Hi R team,
I can create a plot using the code below:
library(ggplot2)
library(dplyr)
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = hwy, color = cyl)) +
geom_point()
ggsave("c:/temp/hwy_cyl.jpg",width = 9, height = 6, dpi = 1200, units = "in")
I want to do the exactly same work using function. Below is the function I
created:
plot1 <- function(y, c, f){
mpg %>%
filter(hwy <35) %>%
ggplot(aes(x = displ, y = mpg[[y]], color = mpg[[c]] )) +
geom_point()
ggsave(paste0("c:/temp/", f ,".jpg"), width = 9, height = 6, dpi =
1200, units = "in")
}
plot1("hwy","cyl","hwy_cyl_f")
But I got error message when I run the code: "Aesthetics must be either length
1 or the same as the data (226): y and colour" . I checked online about the
message. My understanding is: I need to add "fill" in geom_point() statement.
My questions are:
1. is it possible to make the code work without add 'fill' in geom_point()
statement, but keep the color as same as the first code?
2. if I must add 'fill' option in geom_point() statement, how to add them in?
Should I add 266 colors name after 'fill'?
3. this is my first function in R, I'm sure there are many problems in the
code. please point out my error in the code.
Thank you,
Kai
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] mixture univariate distributions fit
Petr: 1. I now am somewhat confused by your goals. Any curve fitting procedure can fit curves to data, including discrete points on a smooth curve. What cannot be done is to recover the exact parameters of the smooth curve from which your data derive, at least not without knowing how the curve was fitted to that underlying (particle size) data, i.e. the nature of the parameterization (if even there was one -- it may just be some sort of empirical smoother like kernel density estimation or some such). 2. mixtools uses EM, so the similarity you noted is probably not surprising. 3. Given my evident confusion, I hope that this email may prompt someone more knowledgeable than I to correct or clarify my "advice." You may wish to further clarify what you wish to do with the parameters that you hope to get to encourage such comments. For example, do you wish to compare the densities you get via their parameterizations? If so, others may be able to offer better strategies to do this, perhaps on SO -- https://stats.stackexchange.com/ -- rather than here. Cheers, Bert Gunter On Thu, Dec 30, 2021 at 12:36 AM PIKAL Petr wrote: > > Thank you Bert > > The values are results from particle size measurement by sedimentation and > they are really available only as these cumulative or density distributions. > What I thought about was that there is some package which could fit data of > such curves and deliver parameters of fitted curves. > > Something like > https://chrisostrouchov.com/post/peak_fit_xrd_python/ > > I found package EMpeaksR which results close to values estimated from mixtools > package. > > test <- spect_em_gmm(temp1$velik, temp1$proc, mu=c(170, 220), > mix_ratio=c(1,1), sigma=c(5,5), maxit=2000, conv.cri=1e-8) > print(cbind(test$mu, test$sigma, test$mix_ratio)) > [,1] [,2] [,3] > [1,] 170.7744 7.200109 0.5759867 > [2,] 229.1815 10.831626 0.4240133 > > But it is probably in stage of intensive development as it is limited in data > visualisation > > Any further hint is appreciated. > > Regards > Petr > > > -Original Message- > > From: Bert Gunter > > Sent: Wednesday, December 29, 2021 5:01 PM > > To: PIKAL Petr > > Cc: r-help mailing list > > Subject: Re: [R] mixture univariate distributions fit > > > > No. > > > > However, if the object returned is the "Value" structure of whatever density > > function you use, it probably contains the original data. You need to check > > the docs to see. But this does not appear to be your situation. > > > > Bert Gunter > > > > "The trouble with having an open mind is that people keep coming along and > > sticking things into it." > > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > > On Wed, Dec 29, 2021 at 3:05 AM PIKAL Petr > > wrote: > > > > > > Dear all > > > > > > I have data which are either density distribution estimate or > > > cummulative density distribution estimate (temp1, temp2 below). I > > > would like to get values (mu, sd) for underlaying original data but they > > > are > > not available. > > > > > > I found mixtools package which calculate what I need but it requires > > > original data (AFAIK). They could be generated from e.g. temp1 by > > > > > > set.seed(111) > > > x<- sample(temp1$velik, size=10, replace=TRUE, prob=temp1$proc) > > > > > > library(mixtools) > > > fit <- normalmixEM(x) > > > plot(fit, which=2) > > > summary(fit) > > > summary of normalmixEM object: > > >comp 1 comp 2 > > > lambda 0.576346 0.423654 > > > mu 170.784520 229.192823 > > > sigma7.203491 10.793461 > > > loglik at estimate: -424062.7 > > > > > > > > > > Is there any way how to get such values directly from density or > > > cummulative density estimation without generating fake data by sample? > > > > > > Best regards > > > Petr > > > > > > > > > temp1 <- structure(list(velik = c(155, 156.8, 157.9, 158.8, 159.6, > > > 160.4, 161.2, 161.9, 162.5, 163.1, 163.8, 164.3, 164.7, 165.3, 165.8, > > > 166.2, 166.7, 167.2, 167.7, 168.2, 168.7, 169.1, 169.6, 170.1, 170.6, > > > 171.1, 171.6, 172, 172.5, 173, 173.5, 174, 174.5, 175.1, 175.7, 176.3, > > > 177, 177.6, 178.3, 179.1, 179.9, 180.6, 181.4, 182.4, 183.5, 184.7, > > > 186.1, 187.9, 189.8, 192, 194.4, 197, 200.1, 203.5, 206.7, 209.2, > > > 211.3, 213.1, 214.8, 216.3, 217.4, 218.5, 219.5, 220.4, 221.3, 222.1, > > > 223, 223.7, 224.5, 225.2, 225.9, 226.7, 227.5, 228.2, 228.9, 229.6, > > > 230.4, 231.2, 231.9, 232.6, 233.4, 234.2, 235, 235.9, 236.8, 237.7, > > > 238.6, 239.7, 241, 242.3, 243.6, 245.2, 247.1, 249.3, 251.9, 255.3, > > > 260, 266, 274.9, 323.4 ), proc = c(0.6171, 1.583, 1.371, 2.13, 1.828, > > > 2.095, 1.994, 2.694, 2.824, 2.41, 2.909, 3.768, 3.179, 3.029, 3.798, > > > 3.743, 3.276, 3.213, 3.579, 2.928, 4.634, 3.415, 3.473, 3.135, 3.476, > > > 3.759, 3.726, 3.9, 3.593, 2.89, 3.707, 4.08, 2.846, 2.685, 3.394, > > > 2.737, 2.693, 2.878, 2.248, 2.368, 2.258, 2.662, 1.866, 1.895, 1.457, > > > 1.513, 1.181, 1.008, 0.9641, 0.799,
Re: [R] mixture univariate distributions fit
Thank you Bert The values are results from particle size measurement by sedimentation and they are really available only as these cumulative or density distributions. What I thought about was that there is some package which could fit data of such curves and deliver parameters of fitted curves. Something like https://chrisostrouchov.com/post/peak_fit_xrd_python/ I found package EMpeaksR which results close to values estimated from mixtools package. test <- spect_em_gmm(temp1$velik, temp1$proc, mu=c(170, 220), mix_ratio=c(1,1), sigma=c(5,5), maxit=2000, conv.cri=1e-8) print(cbind(test$mu, test$sigma, test$mix_ratio)) [,1] [,2] [,3] [1,] 170.7744 7.200109 0.5759867 [2,] 229.1815 10.831626 0.4240133 But it is probably in stage of intensive development as it is limited in data visualisation Any further hint is appreciated. Regards Petr > -Original Message- > From: Bert Gunter > Sent: Wednesday, December 29, 2021 5:01 PM > To: PIKAL Petr > Cc: r-help mailing list > Subject: Re: [R] mixture univariate distributions fit > > No. > > However, if the object returned is the "Value" structure of whatever density > function you use, it probably contains the original data. You need to check > the docs to see. But this does not appear to be your situation. > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > On Wed, Dec 29, 2021 at 3:05 AM PIKAL Petr > wrote: > > > > Dear all > > > > I have data which are either density distribution estimate or > > cummulative density distribution estimate (temp1, temp2 below). I > > would like to get values (mu, sd) for underlaying original data but they > > are > not available. > > > > I found mixtools package which calculate what I need but it requires > > original data (AFAIK). They could be generated from e.g. temp1 by > > > > set.seed(111) > > x<- sample(temp1$velik, size=10, replace=TRUE, prob=temp1$proc) > > > > library(mixtools) > > fit <- normalmixEM(x) > > plot(fit, which=2) > > summary(fit) > > summary of normalmixEM object: > >comp 1 comp 2 > > lambda 0.576346 0.423654 > > mu 170.784520 229.192823 > > sigma7.203491 10.793461 > > loglik at estimate: -424062.7 > > > > > > > Is there any way how to get such values directly from density or > > cummulative density estimation without generating fake data by sample? > > > > Best regards > > Petr > > > > > > temp1 <- structure(list(velik = c(155, 156.8, 157.9, 158.8, 159.6, > > 160.4, 161.2, 161.9, 162.5, 163.1, 163.8, 164.3, 164.7, 165.3, 165.8, > > 166.2, 166.7, 167.2, 167.7, 168.2, 168.7, 169.1, 169.6, 170.1, 170.6, > > 171.1, 171.6, 172, 172.5, 173, 173.5, 174, 174.5, 175.1, 175.7, 176.3, > > 177, 177.6, 178.3, 179.1, 179.9, 180.6, 181.4, 182.4, 183.5, 184.7, > > 186.1, 187.9, 189.8, 192, 194.4, 197, 200.1, 203.5, 206.7, 209.2, > > 211.3, 213.1, 214.8, 216.3, 217.4, 218.5, 219.5, 220.4, 221.3, 222.1, > > 223, 223.7, 224.5, 225.2, 225.9, 226.7, 227.5, 228.2, 228.9, 229.6, > > 230.4, 231.2, 231.9, 232.6, 233.4, 234.2, 235, 235.9, 236.8, 237.7, > > 238.6, 239.7, 241, 242.3, 243.6, 245.2, 247.1, 249.3, 251.9, 255.3, > > 260, 266, 274.9, 323.4 ), proc = c(0.6171, 1.583, 1.371, 2.13, 1.828, > > 2.095, 1.994, 2.694, 2.824, 2.41, 2.909, 3.768, 3.179, 3.029, 3.798, > > 3.743, 3.276, 3.213, 3.579, 2.928, 4.634, 3.415, 3.473, 3.135, 3.476, > > 3.759, 3.726, 3.9, 3.593, 2.89, 3.707, 4.08, 2.846, 2.685, 3.394, > > 2.737, 2.693, 2.878, 2.248, 2.368, 2.258, 2.662, 1.866, 1.895, 1.457, > > 1.513, 1.181, 1.008, 0.9641, 0.799, 0.7878, 0.7209, 0.5869, 0.5778, > > 0.7313, 0.9531, 1.053, 1.317, 1.247, 1.739, 2.064, 1.99, 2.522, 2.401, > > 2.48, 2.687, 2.797, 2.918, 3.243, 3.055, 3.009, 2.89, 3.037, 3.25, > > 3.349, 3.141, 2.771, 2.985, 3.203, 3.298, 3.215, 2.637, 2.683, 2.782, > > 2.632, 2.625, 2.475, 2.014, 1.781, 1.987, 1.627, 1.374, 1.352, 0.9441, > > 1.01, 0.5737, 0.5265, 0.3794, 0.2513, 0.0351)), row.names = 2:101, > > class = "data.frame") > > > > temp2 <- structure(list(velik = c(153.8, 156.3, 157.3, 158.4, 159.2, > > 160.1, 160.8, 161.6, 162.2, 162.8, 163.5, 164, 164.5, 165, 165.5, 166, > > 166.4, 166.9, 167.5, 167.9, 168.5, 168.9, 169.4, 169.8, 170.4, 170.9, > > 171.3, 171.8, 172.2, 172.7, 173.3, 173.8, 174.2, 174.8, 175.5, 176, > > 176.6, 177.3, 177.9, 178.7, 179.5, 180.3, 180.9, 181.9, 182.9, 184.1, > > 185.3, 186.9, 188.8, 190.8, 193.2, 195.6, 198.4, 201.8, 205.3, 208.1, > > 210.3, 212.3, 213.9, 215.7, 216.9, 218, 219.1, 219.9, 220.8, 221.7, > > 222.6, 223.4, 224.1, 224.8, 225.6, 226.3, 227.1, 227.8, 228.5, 229.2, > > 230, 230.8, 231.6, 232.3, 233, 233.7, 234.6, 235.5, 236.3, 237.2, > > 238.1, 239.1, 240.3, 241.6, 242.9, 244.4, 246.1, 248, 250.6, 253.1, > > 257.6, 262.5, 269.5, 280.4, 372.9), proc = c(0, 1, 2, 3, 4, 5, 6, 7, > > 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, > > 26, 27, 28, 29,
