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Hi R users, I need your help to write a code in r that does the following calculation from three different datasets; ac = 1/sum (NPP from date 1 to date 2, dataset=1) * (biomass at date 2 -biomass at date 1, dataset = 2) + (littfall at date 2, dataset=3). all the dates are in yr-month-day format. Which library or function Should I use to tell R do these calculations of these variables at

Hola a todos: Necesito saber si alguien tiene alguna idea de un paquete con múltiples funciones (cálculos) para determinar el tamaño de la muestra (particularmente de estudios de psicología y ciencias sociales). De antemano agradezco la atención. Saludo desde Brasil *Guilherme Amorim Homem de Abreu Loureiro* Agronomist Engineer *CREA-BA: 051511013-2* Master of Science in Crop Production, Soil

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=Stand_Height)); dl=leafbiom$Date[i-1]; de=leafbiom$Date[i];

The model should be class aov or lm and my model class is aovlist. tried tidy from broom library but did not work. To make it class aov, I had to remove the error term; model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) Ahmed Attia, Ph.D. Agronomist & Soil Scientist On Mon, Dec 25, 2017 at 7:38 PM, David Winsemius <dwinsemius at

Hi Ahmed, Your problem appears trivial as you have already specified the form of the calculation. Learn how to "extract" specified elements from a data structure: # first value sum(dataset1$NPP[dataset1$date >= date1 & dataset1$date <= date2]) # second value dataset2$biomass[dataset2$date == date2] - dataset2$biomass[dataset2$date == date1] # third value

Thanks it worked for me. I wanted to plot days since planting on x-axis 1 and years on x-axis 3. LAI_simulation$Date <- as.Date( LAI_simulation$Date, '%Y/%m/%d') LAI_simulation$Date <- as.integer(LAI_simulation$Date - as.Date("2009-10-07")) plot(LAI~Date,data=LAI_simulation,xlab="Days since Oct, 7,

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 height will be multiplied

There are a bunch of things wrong here, although without a reproducible example I can't really fix most of them. - You're overwriting SH within the loop. - You're running the regression 2641 times, even though the result never changes. - 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

Hi Ahmed, When reading from a ncdf file you can use the 'varname', 'lvar' and 'level' arguments - see the 'Details' section in the docs https://www.rdocumentation.org/packages/raster/versions/2.6-7/topics/raster <https://www.rdocumentation.org/packages/raster/versions/2.6-7/topics/raster> We can't tell what is in the ncdf file from what you report other

Hello, I send the message again with the data file as txt because it seems not to be accepted as csv in the R-help list. Data comes from a multiyear field experiment in which 4 levels of a treatment (2, 3, 4, 6) are compared to see the effect on yield. It is a randomized complete block design. The SAS code follows: options ls=95; data uno; infile 'data.txt'

LSD-test produces error for this code; code <- as.factor(Rotationdata_R$`Rot/code`) #factor in the main Nitrogen <- as.factor(Rotationdata_R$Nitrogen) #factor in the sub Rep <- as.factor(Rotationdata_R$REP) #blocks Year <- as.factor(Rotationdata_R$YEAR) #years model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen)+Error(Rep/Year/code),data=Rotationdata_R)

> On Dec 25, 2017, at 2:09 PM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: > > The model should be class aov or lm and my model class is aovlist. > tried tidy from broom library but did not work. To make it class aov, > I had to remove the error term; > > model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) You seemed to have

How can I convert date to continuous variable staring from 1. I tried as.numeric but R starts counting from default January 1, 1970 while my data start Oct 7, 2009. I need to do this conversion to plot the date on two x-axes (1 and 3). Ex; Date LAI 10/7/2009 0 10/8/2009 0.004173 10/9/2009 0.009997 10/10/2009 0.009998 10/11/2009 0.009999 10/12/2009 0.009999 10/13/2009 0.009999 10/14/2009 0.009999

Hello R users, The code below is for loop in R that I want to do to following calculation at each time i and i-1 in 2:75 dataset (Litterfall_Ahmed97). ac = ((LeafBiog at date i -LeafBiog at date i-1, dataset = leafbiom97) + (littperiod at date i, dataset= Litterfall_Ahmed97))/(sum (GPP from date i-1 to date i, dataset=GPP_Ahmed13)/2) . #code for loop GPP_Ahmed13$Date <-

In the model: lm.1 <- lm(variable ~ BLOC + TIL * YEAR , data=selvanera) I found TIL*YEAR interaction significant. Then I am trying to compare means of the different levels of TIL inside every YEAR using: mc.2 <- glht(lm.1, linfct = mcp(TIL*YEAR="Tukey")) summary(mc.2, test = univariate()) but it does not work. There is any way of doing this, like the SLICE option in

S??ren H??jsgaard wrote: > Dear all, > I have used R (Windows) for teaching statistics to agronomists and biologists - and they love R!! Yet there is one immediate short coming of R: The lack of an integrated editor. A plain editor (e.g. similar to notepad in windows) in which people can write their code, highlight the piece of code they wish to "submit" and then press a single key to hav...

Hi I have a netCDF file of volumetric soil water content at four different soil layers and want to convert each soil layer in the netCDF file to a GeoTIFF layer. This code converts the netCDF file to one GeoTIFF layer, i.e. unclear which soil depth. file.nc <- "C:/Soil_Weather_data/Agro/VMC21/VMC21.nc" file.tiff <- "C:/Soil_Weather_data/Agro /VMC21/VMC21" importnetcdf

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,

As an agronomist, sometimes i need to perform statistical analisys on "weird" field data, like 3 or 4 level split plot design. I've read both the help of the program, some books and manual about S and "Venables/Ripley, Modern Applied Statistics with S", but i still have problems in (i suppose) formulae sintax. I'm trying to perform AOV, as explained showed in

As an agronomist, sometimes i need to perform statistical analisys on "weird" field data, like 3 or 4 level split plot design. I've read both the help of the program, some books and manual about S and "Venables/Ripley, Modern Applied Statistics with S", but i still have problems in (i suppose) formulae sintax. I'm trying to perform AOV, as explained in "Random