Hi
I did not get through all answers you already got and you probably obtained
similar advice as mine.
# read data (if you have csv file just use read.csv)
> test<-read.table("clipboard", header=T, sep=",")
# control your object(s)
> str(test)
'data.frame': 8 obs. of 4 variables:
$ date: Fa
Dear Pikal, Deal all,
again really thank.
it seems not working.
Some specifications: My non data are -999, but I could change it.
My final results is:
11 -55.86242 -55.84764660 -277.4775
22 -55.47554 -94.58921682 -277.4845
33 -55.47095 -99.20239198 -277.4709
4
Dear Pikal, DEar all,
I do not if it could help:
if I print MyData%date, I get (at some point)
[281] "1998-12-10 16:00:00 CET" "1998-12-10 17:00:00 CET"
"1998-12-10 18:00:00 CET" "1998-12-10 19:00:00 CET"
[285] "1998-12-10 20:00:00 CET" "1998-12-10 21:00:00 CET"
"1998-12-10 22:00:00 CET" "19
Hi
see in line
From: Diego Avesani
Sent: Wednesday, August 1, 2018 2:30 PM
To: PIKAL Petr
Cc: r-help mailing list
Subject: Re: [R] read txt file - date - no space
Dear Pikal, Deal all,
again really thank.
it seems not working.
Some specifications: My non data are -999, but I could change it
Try this:
> library(lubridate)
> library(tidyverse)
> input <- read.csv(text = "date,str1,str2,str3
+ 10/1/1998 0:00,0.6,0,0
+ 10/1/1998 1:00,0.2,0.2,0.2
+ 10/1/1998 2:00,0.6,0.2,0.4
+ 10/1/1998 3:00,0,0,0.6
+ 10/1/1998 4:00,0
I have a database based on hourly data and I need to forecast next 24h of a
single variable. I was thinking about applying an ARIMA model with some
exogenous variables but I don't succeed to configure the hourly frequency,
estimate ARIMA parameters, pdq ( exists some tests to check which
parameters
Statistics issues are generally off topic here; and we generally prefer
posters to show us their own efforts rather than expecting us to solve the
problem for them.
However, this CRAN time series task view may be useful to you:
https://cran.r-project.org/web/views/TimeSeries.html
Cheers,
Bert
I have 6 variables, (A,B,C,D,E,F) that can either pass or fail (i.e., true
or false).
I can get a table of all pass/fail combinations with this:
scenarios <- expand.grid(A = c("pass", "fail"), B = c("pass", "fail"), C =
c("pass", "fail"), D = c("pass", "fail"), E = c("pass", "fail"), F =
c("pass",
Hello,
I am interested to apply an econometric technique of Latent Variable
framework on Environmental Kuznets Curve for 164 countries for a span of 25
years.
The methodology and the code are from Simulation exercise from an
unpublished paper "Two Examples of Convex-Programming-Based
High-Dimens
On Wed, 1 Aug 2018 17:40:54 +0200
Edoardo Silvestri wrote:
> I have a database based on hourly data and I need to forecast next
> 24h of a single variable. I was thinking about applying an ARIMA
> model with some exogenous variables but I don't succeed to configure
> the hourly frequency, estimat
Hi Rod,
How about this?
scenarios <- expand.grid(A = c("pass", "fail"), B = c("pass", "fail"), C =
c("pass", "fail"), D = c("pass", "fail"), E = c("pass", "fail"))
scenarios$F<-ifelse(scenarios$E=="pass","fail","pass")
Jim
On Thu, Aug 2, 2018 at 11:20 AM, R Stafford wrote:
> I have 6 variable
Dear
I have check the one of the line that gives me problem. I mean, which give
NA after R processing. I think that is similar to the others:
10/12/1998 10:00,0,0,0
10/12/1998 11:00,0,0,0
10/12/1998 12:00,0,0,0
10/12/1998 13:00,0,0,0
10/12/1998 14:00,0,0,0
10/12/1998 15:00,0,0,0
10/12/1998 16:00,
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