?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.
>>>
>>> [[alternative HTML version deleted]]
>>>
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see
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>>> PLEASE do read the posting guide
>> 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
