similar to: Date Time conversion

Hi All, I have a scatter plot produced using ggplot2 and I want to add the regression line to this scatter plot. I suppose I can use geom_smooth() to do this, but for the sake of learning ( I am new both to R and ggplot2), I want to try and add it as a function (something that curve() does in the standard R plotting). I did some search and found that stat_function() can be used for this. But

Hi, I'm trying to understand some details about an example maintened in [1]. According that link, I have total.data as a data set (am I right?). But I don't understand how is built that table. I saved the dataset in a file, with dput(), and had something like this: structure(list(df.all = structure(list(V1 = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,

Hi R-Help, data at bottom I've been struggling with a problem where I need to order based on 1) the Frequency "Freq" and 2) keeping each group of 3 of the same type together "Var2" but I want across all groups it to go "high to low" based on the earn factor. Thank you! structure(list(Var1 = structure(c(1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L,

Hi, Try this: #mat1 is the data res<-do.call(cbind,lapply(seq_len(nrow(mat1)),function(i) {new1<-do.call(rbind,lapply(seq_len(nrow(mat1[-i,])),function(j) {x1<-rbind(mat1[i,],mat1[j,]); x2<-(abs(x1[1,1]-x1[2,1])*abs(x1[1,5]-x1[2,5]))+(abs(x1[1,2]-x1[2,2])*abs(x1[1,6]-x1[2,6]))+(abs(x1[1,3]-x1[2,3])*abs(x1[1,7]-x1[2,7]))+(abs(x1[1,4]-x1[2,4])*abs(x1[1,8]-x1[2,8]))}));new1}))

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

Hi all: I am trying to use the ddply function to estimate the mean of 'Total','Fry','Smolt' and 'Fry.Eq' columns without success. I have the dput of my dataset below. I wonder if someone can give me a hand with this function. # dput(winter) winter <-structure(list(IDDate = structure(c(37L, 48L, 59L, 62L, 63L, 64L, 65L, 66L, 67L, 38L, 39L, 40L, 41L, 42L, 43L,

Hi all, I would like to ask you for help. I did a dotplot - using dotchart function. There are two localites (loc) with values 75 or 56 in my data ZZ. The f column has 4 levels: P1, S1, S8, R6. The dataframe is ordered by N value, pchloc value is assign to use "pch" in plot. > head(ZZ) loc f N color ordered pchloc 98 75 S1 6.39 green 1 16 99 75 S8 6.44 blue

Hello, I want to use lme to fit two (or more) models, and then compare the fits on each individual. I know how to write my own code to do this (for each individual, plot the raw data, followed by lines() to plot each fitted curve) but I would like to use plot(augPred(... as it produces a nice trellis plot. I thought I could do this with par(new=T) but it does not seem to work.

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

Dear R user I want to create a table (as below) to summarize the attached data (Test.csv, which can be read into R by using 'read.csv(Test.csv, header=F)' ), to indicate the day that there are any data available, e.g.value=1 if there are any data available for that day, otherwise value=0. 28/04 29/04 30/04 01/05 02/05 532703 0 1 1

I'm trying to read a binary file created by a fortran code using readBin and readChar. Everything reads fine (integers and strings) except for double precision numbers, they are read as huge or very small number (1E-250,...). I tried various endianness, swap, But nothing has worked so far. I also tried on R 64 bit for linux and windows (R 2.14) and R 2.11 on windows XP 32 bit. Any help would

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 there, I am having a little problem with combining three scale_manual commands in a facet plot. I am not able to combine the three different characteristics, instead ending up with three different descriptions next to the graph for the same geom. I would like to see two separate labels (not three); one describing lines 1-7 and the other 8-14. For each of the treatments (A-B) I want a

I have the following data (a subset of the real data set): structure(list(Date = structure(c(1209625080, 1209641460, 1209652500, 1209676800, 1209682860, 1209692100, 1209706980, 1209722580, 1209726300, 1209739620, 1209762780, 1209765720, 1209770520, 1209791040, 1209812580, 1209829920, 1209837180, 1209848160, 1209854640, 1209859440, 1209870780, 1209887760, 1209901080, 1209921660, 1209929280,

Folks, I have a data frame with columns 200401, 200402, ..., 201207, 201208. These represent years/months. What would be the best way to sum these columns by year? What about by quarter? Thanks for your time, KW -- [[alternative HTML version deleted]]

I can't get my simultaneous equations to work using system fit. Please help. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) str(Empdata) Empdata$gnipc<-as.numeric(Empdata$gnipc) install.packages("systemfit") library("systemfit") pdata <- plm.data(Empdata,

I'm creating a lattice barchart based off a pretty complicated data structure. The barchart comes out quite nice ( thanks to lattice ) but the problem is that the horizontal axis comes out all scrunched because the barchart doesn't know that the intervals of Var.1 are really "associated" with the conditioning variable Var.2. Therefore, all the intervals of Var.1 are put on

Dear friends, I have a weekly time series which starts on Jan 4th, 2003 and ends on december 31st, 2016. I set up my ts object as follows: MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) MyModel <- auto.arima(MyTseries, d=1, D=1) MyModelForecast <- forecast (MyModel, h=12) Since my last observation was on december 31st, 2016 I expected my forecast date to start on

> On Dec 6, 2017, at 5:07 AM, Paul Bernal <paulbernal07 at gmail.com> wrote: > > Dear friends, > > I have a weekly time series which starts on Jan 4th, 2003 and ends on > december 31st, 2016. > > I set up my ts object as follows: > > MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) > > MyModel <- auto.arima(MyTseries, d=1, D=1)

Thank you very much David. As a matter of fact, I solved it by doing the following: MyTimeSeriesObj <- ts(MyData, freq=365.25/7, start=decimal_date(mdy("01-04-2003"))) After doing that adjustment, my forecasts dates started from 2017 on. Cheers, Paul 2017-12-06 12:03 GMT-05:00 David Winsemius <dwinsemius at comcast.net>: > > > On Dec 6, 2017, at 5:07 AM, Paul