Hi
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Kapil Shukla
Sent: Saturday, March 01, 2014 6:23 PM
To: r-help@r-project.org
Subject: [R] Time Series Data Analysis
Hi All
I am totally new to R so this question may
Hi All
I am totally new to R so this question may sound basic to many of you. I am
trying to use R for time series analysis of some financial instruments.
Currently i have hourly data of a stock which has OPEN/HIGH/LOW/CLOSE in a
CSV file. I used read.table to import the data in R in to a
For a set of data showing seasonality (related to the 4th quarter),
ncv
test shows p-value of 0.008 which rejects the null hypothesis of
constant-variance. Currently a linear LM relationship is being
applied to
the data.
Should white's error be used to correct the
For a set of data showing seasonality (related to the 4th quarter), ncv
test in R shows p-value of 0.008 which rejects the null hypothesis of
constant-variance. How to apply White's standard error in R?
thanks
__
The
On 26.08.2011 17:43, Simmons, Ryan wrote:
I am working with data from the USGS with data every 30 minutes from
4/27/2011 to 8/25/2011.
I am having trouble with setting the frequency.
My R script is below:
shavers=read.csv(shavers.csv)
names(shavers)
[1] agency_cdsite_no
I am working with data from the USGS with data every 30 minutes from
4/27/2011 to 8/25/2011.
I am having trouble with setting the frequency.
My R script is below:
shavers=read.csv(shavers.csv)
names(shavers)
[1] agency_cdsite_no datetime tz_cdTemp
[6]
I have a stock price dataset a snippet of which is:
plcm60[1:15, c(1,3,4,5,6,7)]
DATE BIDLO ASKHIPRC VOL RET
1 1/2/03 9.450 9.79 9.700 1531819 0.018907
2 1/3/03 9.670 9.94 9.940 1582192 0.024742
3 1/6/03 9.830 10.05 9.960 1843298 0.002012
4 1/7/03 9.835
Hi:
Perhaps something like this, assuming DATE is a Date object (try str(plcm60)
to check) - if not, you need to use as.Date() to convert.
jandays - data.frame(DATE = seq(as.Date('2003-01-01'), by = 'days', length
= 23))
merge(jandays, plcm60, by = 'DATE', all.x = TRUE)
HTH,
Dennis
On Wed, Nov
On 10/25/2010 09:37 PM, Gabor Grothendieck wrote:
On Tue, Oct 26, 2010 at 12:28 AM, Bob Cunninghamflym...@gmail.com wrote:
I have time-series data from a pair of inexpensive self-logging 3-axis
accelerometers (http://www.gcdataconcepts.com/xlr8r-1.html). Since I'm not
sure of the
From: ggrothendi...@gmail.com
Date: Tue, 26 Oct 2010 00:37:05 -0400
To: flym...@gmail.com
CC: r-help@r-project.org
Subject: Re: [R] Time series data with dropouts/gaps
On Tue, Oct 26, 2010 at 12:28 AM, Bob Cunningham wrote:
I have time
I have time-series data from a pair of inexpensive self-logging 3-axis
accelerometers (http://www.gcdataconcepts.com/xlr8r-1.html). Since I'm not
sure of the vibration/shock spectrum I'm measuring, for my initial sensor
characterization run the units were mounted together with the sample rate
On Tue, Oct 26, 2010 at 12:28 AM, Bob Cunningham flym...@gmail.com wrote:
I have time-series data from a pair of inexpensive self-logging 3-axis
accelerometers (http://www.gcdataconcepts.com/xlr8r-1.html). Since I'm not
sure of the vibration/shock spectrum I'm measuring, for my initial sensor
Dear Sir/madam
I am a new user to R. I have no background in coding or even
scripting. It seems as if R would be the best tool in order to analyse
large sets of data. I need to sum hourly readings for the day and then
sum daily into monthly readings. i also need to do the same for
another set of
On Mar 20, 2010, at 1:17 PM, Gaathier Mahed wrote:
Dear Sir/madam
I am a new user to R. I have no background in coding or even
scripting. It seems as if R would be the best tool in order to analyse
large sets of data. I need to sum hourly readings for the day and then
sum daily into monthly
Hi All,
I'm trying to analyze some time series data and I have run into difficulty. I
have decadal sun spot data and I want to separate the very regular periodic
function from the trend and noise. I looked into using stl(), but the frequency
of the time series data must be greater than 1 for
On Nov 27, 2009, at 9:55 AM, chris carleton wrote:
Hi All,
I'm trying to analyze some time series data and I have run into
difficulty. I have decadal sun spot data and I want to separate the
very regular periodic function from the trend and noise. I looked
into using stl(), but the
-project.org
From: dwinsem...@comcast.net
To: w_chris_carle...@hotmail.com
Subject: Re: [R] Time Series Data
Date: Fri, 27 Nov 2009 10:10:36 -0500
On Nov 27, 2009, at 9:55 AM, chris carleton wrote:
Hi All,
I'm trying to analyze some time series data and I have run into
difficulty
Hi all and thanks in advance.
I am regressing Time and Weight, and then predicting Weight at
different Time. The format of the Time data is day/month/year. How
can I get R to use time series data such as this?
Keith
--
M. Keith Cox, Ph.D.
Alaska NOAA Fisheries, National Marine Fisheries
jullian day?
On Mon, Oct 19, 2009 at 1:20 PM, Marlin Keith Cox marlink...@gmail.com wrote:
Hi all and thanks in advance.
I am regressing Time and Weight, and then predicting Weight at
different Time. The format of the Time data is day/month/year. How
can I get R to use time series data
If you convert your dates to an object d of Date class then
as.numeric(d) will be the number of days since the Epoch. See R News
4/1.
On Mon, Oct 19, 2009 at 2:20 PM, Marlin Keith Cox marlink...@gmail.com wrote:
Hi all and thanks in advance.
I am regressing Time and Weight, and then
Check out na.locf in the zoo package. Here we fill in
NAs going forward and just in case there were NAs
right at the beginning we fill them in backward as well.
library(zoo)
x - as.Date(c(NA, 2000-01-01, NA))
x2 - na.locf(x, na.rm = FALSE)
x2 - na.locf(x2, fromLast = TRUE, na.rm = FALSE)
gives:
Dear list,
I have some problems with time-series data and missing values of time-invariant
informations like sex or the birth-date.
Assume a data (d) structure like
id birth sex year of observation
1 NA NA 2006
1 1976-01-01 male2007
1
22 matches
Mail list logo
