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