similar to: Gamma distribution parameter estimation

Dear arun and all R users, I will first of all try to simply define my issue.. I have data in the following format Year Discharge dd/mm/yyyy x .. … … … There are some NA values in the discharge which I would like to predict by using “predict command”. I cant figure out the way to write the coding for that. Could you please help me on that??? I have also ,written

Dear R Users, Could you please help me on the following issue? I have a real large yearly data set. For each year I have 365 flow values. Some of the flow values are not known and that’s why you will see NA written in those slots. I wanted to know, is there a way that I can estimate those values? I tried approx command but it seems least helpful for the kind of issue I am up against.

> Dear list, > > I have some data on a geneaology, here is a subset: > warmerge[1:11,c(1,6,25)] > Warrior SibID birth.year > 1100 3793 2013 1926 > 4 2013 2024 1934 > 1094 3769 2024 1918 > 632 2747 2037 1928 > 176 2083 2039 1944 > 187 2085 2039 1949 > 192 2086 2039 NA > 495

Dear R users, [in case the format of email is changed or you dont finf it easy to understand, i have attached a text file of my question] i have the data in the following format and i want to convert it in the format given at the end. Ta ans Sa are the names of certain cities. there are 69 cities in my data. column 1 is representing station name (i am writing the data of only two cities for

I have a challenge that I want to share with the group. This is not homework (but I may assign it as such if I teach the appropriate class again) and I have found one solution, so don't need anything urgent. This is more for fun to see if others can find a better solution than I did. The challenge: I want to read a book in a given number of days. I want to read an integer number of

Hello, I'm trying to convert a character column in several dataframes to lower case. ### # # Sample data and 'spp' column summaries: # dput(ban.ovs.1993[sample(row.names(ban.ovs.1993), 20), 1:4]) ban.ovs.93 <- structure(list(oplt = c(43L, 43L, 38L, 26L, 35L, 8L, 39L, 1L, 34L, 50L, 10L, 29L, 31L, 24L, 18L, 12L, 27L, 49L, 28L, 51L), rplt = c(NA_integer_, NA_integer_,

Hello, I have data in the following form age sex Int.Prev.Est.1 Int.Prev.Est.2 Int.Prev.Est.3 Int.Prev.Est.4 Int.Prev.Est.5 93110 93 0 23.75482 57.86592 9.755003 4.343534 4.280714 93610 93 1 53.36475 39.47247 4.381618 1.622119 1.159044 94110 94 0 23.47514 58.23936 10.789339 3.690415 3.805741 94610 94 1

Hello folks, I have a big project to work on and the dataset is classified so I am just going to use my own example so everyone can understand what I am targeting. Let's take Target as an example: We consider three brands of tape: Target brand, 3M and Avery. The original data frame has 4 columns: Year of Record, Product_Name(which contains three brands of tape), Sales, and Region. I want to

Responses should be copied to r-help using ReplyAll. You are still sending html formatted emails. If you are using Microsoft Outlook, click the Format Text tab and select ?Aa Plain Text?. No one has asked you to reveal the data set, only to create one with a similar structure. Is the data I sent reasonably close? What should it look like after it is transformed? David C From: nguy2952

No html!, Copy the list using Reply-All. The data frame group_PrivateLabel does not contain variables called Product_Name or Region. David C From: nguy2952 University of Minnesota <nguy2952 at umn.edu> Sent: Friday, June 1, 2018 2:13 PM To: David L Carlson <dcarlson at tamu.edu> Subject: Re: [R] Regroup and create new dataframe Hi David, your example is perfect! I am still

Hi Dennis, SOLVED!!! My thanks to both you, John, and others who chimed in. Took a little more digging before finally working, but it is working! Here's a little more of what I did and the ultimate resolutions: I installed the reshape2 library from CRAN. Executed > (.packages()) [1] "reshape2" "stats" "graphics" "grDevices"

R experts, I am working with a fairly large data set comprised of 563 rows by 116 columns including several different modes. I have been unable to read in the data set completely using the read.table function and the RGui (i.e. nearly half the total number of rows are missing from the data set along with the column names). The data does read in fully using Tinn-R's Rterm; however, at several