Reg: Frequency in declaring time series data
?s 20:52 de 16/01/2023, Upananda Pani escreveu:
Hi Rui, Thank you so much for your help. As I have to fit a Markov Switching Model using MSwM package. May I know whether i can convert from zoo object to a time series object. As I have to use several packages which uses ts so I am not able to decide how to do it. Grateful to you for your help and support. With sincere regards, Upananda On Tue, 17 Jan, 2023, 01:40 Rui Barradas, <ruipbarradas at sapo.pt> wrote:
?s 16:39 de 16/01/2023, Upananda Pani escreveu:
Dear All, I have a time series daily data with date are stored ( %dd-%mm-%yy
format )
from 22-01-20 to 03-08-21. In total I have 560 observations. I am using
the
following command to declare as a time series object. Here the the data
set
is 7 days a week.
oil <- read_xlsx("crudefinal.xlsx")
pricet=ts(oil$price, start = c(2020, 22), freq = 365)
roilt=ts(diff(log(oil$price))*100,start=c(2020,22), freq=365)
Shall I have to declare the dates here? I want to know also if it is a 5
day trading a week, how to declare the frequency.
Looking forward to your reply
Regards,
Upananda Pani
Looking forward to your suggestions.
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http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Hello, Package zoo is the best way of having dates in a time series. The package comes with several vignettes that can get you started quickly. See the difference between classes ts and zoo below. # make up some test data oil <- data.frame(price = cumsum(rnorm(560))) oil$date <- seq(as.Date("2020-01-22"), by = "1 day", length.out = 560) # base R pricet <- ts(oil$price, start = c(2020, 22), freq = 365) time(pricet) index(pricet) plot(pricet) #--- library(zoo) library(ggplot2) pricez <- zoo(oil$price, order.by = oil$date) time(pricez) index(pricez) autoplot(pricez) vignette(package = "zoo") Hope this helps, Rui Barradas
Hello,
Please always cc the R-Help list.
I have no experience with package MSwM but according to the
vignette("example", package = "MSwM")
you first fit a regression model, say 'mod', and then fit an
Autoregressive Markov Switching Model to mod. You don't need a time
series, only a regression fit.
Hope this helps,
Rui Barradas