Assuming the input data.frame, DF, is of the form shown reproducibly
in the Note below, to convert the series to zoo or ts:
library(zoo)
# convert to zoo
z <- read.zoo(DF)
# convert to ts
as.ts(z) #
Note:
DF <- structure(list(year = c(1980, 1981, 1982, 1983, 1984), cnsm = c(174,
175, 175, 172, 173), incm = c(53.4, 53.7, 53.5, 53.2, 53.3),
with = c(60.3, 60.5, 60.2, 60.1, 60.7)), .Names = c("year",
"cnsm", "incm", "with"), row.names = c(NA, -5L),
class = "data.frame")
On Sat, Sep 16, 2017 at 8:10 AM, yadav neog <yadavneog at gmail.com>
wrote:> oky.. thank you very much to all of you
>
>
> On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at
gmail.com> wrote:
>
>> You can just use the same code that I provided before but now use your
>> dataset. Like this
>>
>> df <- read.csv(file="data2.csv",header=TRUE)
>> dates <- as.Date(paste(df$year,"-01-01",sep=""))
>> myXts <- xts(df,order.by=dates)
>> head(myXts)
>>
>> #The last command "head(myXts)" shows you the first few rows
of the xts
>> object
>> year cnsm incm wlth
>> 1980-01-01 1980 173.6527 53.3635 60.3013
>> 1981-01-01 1981 175.4613 53.6929 60.4980
>> 1982-01-01 1982 174.5724 53.4890 60.2358
>> 1983-01-01 1983 171.5070 53.2223 60.1047
>> 1984-01-01 1984 173.3462 53.2851 60.6946
>> 1985-01-01 1985 171.7075 53.1596 60.7598
>>
>>
>> On Sat, Sep 16, 2017 at 9:55 AM, Berend Hasselman <bhh at
xs4all.nl> wrote:
>>
>>>
>>> > On 15 Sep 2017, at 11:38, yadav neog <yadavneog at
gmail.com> wrote:
>>> >
>>> > hello to all. I am working on macroeconomic data series of
India, which
>>> in
>>> > a yearly basis. I am unable to convert my data frame into time
series.
>>> > kindly help me.
>>> > also using zoo and xts packages. but they take only monthly
>>> observations.
>>> >
>>> > 'data.frame': 30 obs. of 4 variables:
>>> > $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989
...
>>> > $ cnsm: num 174 175 175 172 173 ...
>>> > $ incm: num 53.4 53.7 53.5 53.2 53.3 ...
>>> > $ wlth: num 60.3 60.5 60.2 60.1 60.7 ...
>>> > --
>>>
>>> Second try to do what you would like (I hope and think)
>>> Using Eric's sample data
>>>
>>> <code>
>>> zdf <- data.frame(year=2001:2010,
cnsm=sample(170:180,10,replace=TRUE),
>>> incm=rnorm(10,53,1), wlth=rnorm(10,60,1))
>>> zdf
>>>
>>> # R ts
>>> zts <- ts(zdf[,-1], start=zdf[1,"year"])
>>> zts
>>>
>>> # turn data into a zoo timeseries and an xts timeseries
>>>
>>> library(zoo)
>>> z.zoo <- as.zoo(zts)
>>> z.zoo
>>>
>>> library(xts)
>>> z.xts <- as.xts(zts)
>>> z.xts
>>> </code>
>>>
>>> Berend Hasselman
>>>
>>> > Yadawananda Neog
>>> > Research Scholar
>>> > Department of Economics
>>> > Banaras Hindu University
>>> > Mob. 9838545073
>>> >
>>> > [[alternative HTML version deleted]]
>>> >
>>> > ______________________________________________
>>> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>> > https://stat.ethz.ch/mailman/listinfo/r-help
>>> > PLEASE do read the posting guide
http://www.R-project.org/posti
>>> ng-guide.html
>>> > and provide commented, minimal, self-contained, reproducible
code.
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posti
>>> ng-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>
>
>
> --
> Yadawananda Neog
> Research Scholar
> Department of Economics
> Banaras Hindu University
> Mob. 9838545073
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com
thankx to everyone for your valuable suggestions. one query regarding the GARCH model. I have applied the GARCH model for the same data that I send you all . and my results coming like Error in .sgarchfit(spec = spec, data = data, out.sample = out.sample, : ugarchfit-->error: function requires at least 100 data points to run can you suggest something on it. On Fri, Sep 22, 2017 at 6:02 AM, Gabor Grothendieck <ggrothendieck at gmail.com> wrote:> Assuming the input data.frame, DF, is of the form shown reproducibly > in the Note below, to convert the series to zoo or ts: > > library(zoo) > > # convert to zoo > z <- read.zoo(DF) > > # convert to ts > as.ts(z) # > > > Note: > > DF <- structure(list(year = c(1980, 1981, 1982, 1983, 1984), cnsm = c(174, > 175, 175, 172, 173), incm = c(53.4, 53.7, 53.5, 53.2, 53.3), > with = c(60.3, 60.5, 60.2, 60.1, 60.7)), .Names = c("year", > "cnsm", "incm", "with"), row.names = c(NA, -5L), class = "data.frame") > > > On Sat, Sep 16, 2017 at 8:10 AM, yadav neog <yadavneog at gmail.com> wrote: > > oky.. thank you very much to all of you > > > > > > On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at gmail.com> > wrote: > > > >> You can just use the same code that I provided before but now use your > >> dataset. Like this > >> > >> df <- read.csv(file="data2.csv",header=TRUE) > >> dates <- as.Date(paste(df$year,"-01-01",sep="")) > >> myXts <- xts(df,order.by=dates) > >> head(myXts) > >> > >> #The last command "head(myXts)" shows you the first few rows of the xts > >> object > >> year cnsm incm wlth > >> 1980-01-01 1980 173.6527 53.3635 60.3013 > >> 1981-01-01 1981 175.4613 53.6929 60.4980 > >> 1982-01-01 1982 174.5724 53.4890 60.2358 > >> 1983-01-01 1983 171.5070 53.2223 60.1047 > >> 1984-01-01 1984 173.3462 53.2851 60.6946 > >> 1985-01-01 1985 171.7075 53.1596 60.7598 > >> > >> > >> On Sat, Sep 16, 2017 at 9:55 AM, Berend Hasselman <bhh at xs4all.nl> > wrote: > >> > >>> > >>> > On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: > >>> > > >>> > hello to all. I am working on macroeconomic data series of India, > which > >>> in > >>> > a yearly basis. I am unable to convert my data frame into time > series. > >>> > kindly help me. > >>> > also using zoo and xts packages. but they take only monthly > >>> observations. > >>> > > >>> > 'data.frame': 30 obs. of 4 variables: > >>> > $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... > >>> > $ cnsm: num 174 175 175 172 173 ... > >>> > $ incm: num 53.4 53.7 53.5 53.2 53.3 ... > >>> > $ wlth: num 60.3 60.5 60.2 60.1 60.7 ... > >>> > -- > >>> > >>> Second try to do what you would like (I hope and think) > >>> Using Eric's sample data > >>> > >>> <code> > >>> zdf <- data.frame(year=2001:2010, cnsm=sample(170:180,10, > replace=TRUE), > >>> incm=rnorm(10,53,1), wlth=rnorm(10,60,1)) > >>> zdf > >>> > >>> # R ts > >>> zts <- ts(zdf[,-1], start=zdf[1,"year"]) > >>> zts > >>> > >>> # turn data into a zoo timeseries and an xts timeseries > >>> > >>> library(zoo) > >>> z.zoo <- as.zoo(zts) > >>> z.zoo > >>> > >>> library(xts) > >>> z.xts <- as.xts(zts) > >>> z.xts > >>> </code> > >>> > >>> Berend Hasselman > >>> > >>> > Yadawananda Neog > >>> > Research Scholar > >>> > Department of Economics > >>> > Banaras Hindu University > >>> > Mob. 9838545073 > >>> > > >>> > [[alternative HTML version deleted]] > >>> > > >>> > ______________________________________________ > >>> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >>> > https://stat.ethz.ch/mailman/listinfo/r-help > >>> > PLEASE do read the posting guide http://www.R-project.org/posti > >>> ng-guide.html > >>> > and provide commented, minimal, self-contained, reproducible code. > >>> > >>> ______________________________________________ > >>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >>> https://stat.ethz.ch/mailman/listinfo/r-help > >>> PLEASE do read the posting guide http://www.R-project.org/posti > >>> ng-guide.html > >>> and provide commented, minimal, self-contained, reproducible code. > >>> > >> > >> > > > > > > -- > > Yadawananda Neog > > Research Scholar > > Department of Economics > > Banaras Hindu University > > Mob. 9838545073 > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > -- > Statistics & Software Consulting > GKX Group, GKX Associates Inc. > tel: 1-877-GKX-GROUP > email: ggrothendieck at gmail.com >-- Yadawananda Neog Research Scholar Department of Economics Banaras Hindu University Mob. 9838545073 [[alternative HTML version deleted]]
On Fri, Sep 22, 2017 at 7:28 AM, yadav neog <yadavneog at gmail.com> wrote:> thankx to everyone for your valuable suggestions. one query regarding the > GARCH model. > I have applied the GARCH model for the same data that I send you all . and > my results coming like > > Error in .sgarchfit(spec = spec, data = data, out.sample = out.sample, : > > ugarchfit-->error: function requires at least 100 data > points to run > > can you suggest something on it. >The error is protecting you from the unreliable results that you would get by running the model on too few observations. You either need more data, or a different algorithm (not GARCH).> > > > -- > Yadawananda Neog > Research Scholar > Department of Economics > Banaras Hindu University > Mob. 9838545073 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Joshua Ulrich | about.me/joshuaulrich FOSS Trading | www.fosstrading.com R/Finance 2017 | www.rinfinance.com