similar to: declaring constants in an Sweave / LaTeX document

Displaying 20 results from an estimated 200 matches similar to: "declaring constants in an Sweave / LaTeX document"

2012 Jan 18
0
Time series questions
Hi, I am trying to teach myself some time series analysis. I have some time series data on GDP, quarterly, from 1947 to 2011. colnames are "Year" "Quarter" "GDP" and "GDP.deflator" The first problem I have is that 4th quarter 2010 is missing--not even NA, there is no record for Year=2010 and Quarter =4, so instead of 260 rows, I only have 259. To solve
2004 Apr 14
3
A bug report?
Folks, I have a strange situation, which I may have isolated as a bug report. Or, it could just be that there's something about R that I don't know. :-) I have attached the data file and the program file but don't know whether these attachments will make it into the list. Here is my bugreport.R program -- ---------------------------------------------------------------------------
2008 Jan 30
2
numeric coercion when one or more elements is non numerice
I don't understand this behavior. Why does the every data point get trashed by data.matrix when there is one non-numeric element in the array? Thanks. > temp GDP CPIYOY 19540 2098.1 garbage 19632 2085.4 0.9 19724 2052.5 0.8 19814 2042.4 1.1 > data.matrix(temp) GDP CPIYOY 19540 4 4 19632 3 2 19724 2 1 19814 1
2001 Sep 24
3
x axis point labels
I am attempting to manually specify x axis value labels (NOT x axis label as in xlab) on a density plot. Generally speaking, I would like to erase the default x axis point labels and replace them with arbitrary x axis point labels relating to specific CDF points. I am sure this can be done, but it isn't obvious to me how. Has anyone done this before? My R code follows if it helps (new
2012 Apr 30
5
Different varable lengths
Hi! I'm trying to do a lm() test on three objects. My problem is that R protests and says that the variable lengths differ for one of the objects (Sweden.GDP.gap). But I have double checked that the number of observations are the same. All three objects should contain 9 observations but R only accepts 9 observations in two of the objects. The third must have 10! Very confusing because there
2011 Dec 07
1
removing specified length of text after a period in dataframe of char's
Dear all, I'm trying to remove some text after the period (a decimal point) in the data frame 'hi', below. This is one step in formatting a table. So I would like e.g. "2.0" to become "2" and "5.3" to be "5.3", where the variable digordered contains the number of digits after the decimal that I would like to display, in the same order in which
2012 Oct 22
0
"Vars" package: impulse response function
Hello, I'm using VAR models in R in order to obtain impulse responses of stock market shock on US economy. I have series of quarterly changes in real gdp, S&P 500 and quarterly level of unemployment for 1985 - 2012 period. My series are stationary. So I did all the steps below. However I don't understand what do irf function results mean. These are the cumulative orthogonal responses
2003 Oct 04
2
(no subject)
Dear all, I have the following question. I have to fit the hierarchical model for the hypothesis concern the individual-level effects by controlling for the individual -level attributes and national-level contextual effects on individuals by using R. O have to obtain the estimates of the impact of the second-level (national: GDP per capita) effects on individuals ( in this instance the impact
2011 Nov 16
1
geom_bar with missing data in package ggplot
Dear all, I was hoping someone could help with a ggplot question. I would like to generate a faceted bar chart, but missing data are causing problems. g<-structure(list(Date = structure(c(11322, 11687, 12052, 11322, 11687, 12052, 11322, 11687, 12052, 11322, 11687, 12052), class = "Date"), variable = c("Govt Revenues to GDP", "Govt Revenues to GDP",
2001 May 06
1
legend/text in time series plot
hi, i need help on placing legend/text in a time series plot. here is what i am doing (i am using rw1022 on windoze 2000): #read data file gdpn <- scan("jngdpsa.dat", list(year=0, qtr=0, gdp=0)); gdpr <- scan("jrgdpsa.dat", list(year=0, qtr=0, gdp=0)); #convert to time series object gdpn <- ts(gdpn$gdp, frequency=4, start=c(1955,2)); gdpr <- ts(gdpr$gdp,
2002 Jun 14
1
data.frame - transform
Hi there, I have a data.frame (pwt6) which I would like to transform: country year gdp MEX 1950 2 MEX 1951 5 BOL 1950 4 BOL 1951 12 ITA 1950 45 ITA 1951 2 This should be the result: year MEX.gdp BOL.gdp ITA.gdp 1950 2 4 45 1951 5 12 2 Right now I have this code (better - no code): country.label<-names(table(pwt6$country)) result<-data.frame(year=NULL) for(i in country.label) ?
2005 Oct 31
2
What is the history of CONFIG_EXT{2,3}_CHECK?
Can anyone tell me the history of CONFIG_EXT{2,3}_CHECK? There is code for a "check" option for mount if these options are enabled, but there's no way to enable them. TIA Adrian -- "Is there not promise of rain?" Ling Tan asked suddenly out of the darkness. There had been need of rain for many days. "Only a promise," Lao Er said.
2007 Apr 25
0
sorting data help
I am trying to create a 2x2xk contingency table. The variables are GDP and an income inequality statistic with year being the k levels. I want to eventually run a loglinear model with the data. Currently the data is organized by either year or country. example Country Year log(GDP) sqrt(INEQ) 1 1980 24 5.3 1 1981 25 5.45 1
2011 Aug 04
1
Running a column loop through the Moran.I function.
Dear R users, I have two data frames that consist of statistical information for most countries around the world. One dataframe consists of the latitude and longitude ("coord.csv") of each country, while the other consists of 100's of different attributes ("countryattri.csv") for each country (like, GDP, Population, etc.). The data is organized with a header and then
2013 Jul 11
1
Testing for weak exogeneity in a SUR ECM
Dear all, I have set up a Labour Demand Error Correction Model for some German federal states. As I expect the labour markets to be correlated I used a Seemingly Unrelated Regression using systemfit in R. My Model is: d(emp)_it = c + alpha*ln(emp)_i,t-1 + beta_1*ln(gdp)_i,t-1 + + beta_2*ln(wage)_i,t-1 + + beta_1*ln(i)_i,t-1 + gamma_1*d(gdp)_it + gamma_2*d(wage)_it with emp_it being the
2011 Jun 26
2
Accessing variables in a data frame
Hello My data.frame (dat) contains many variables named var.names and others named var.names_var.id For example var.name <- c("gdp","inf","unp") var.id <- c("w","i") x <- paste(var.name, rep(var.id, each=length(var.name)), sep="_") How can I access variables in the dama.frame by names listed in x, for example to compute
2013 May 04
2
Lasso Regression error
Hi all, I have a data set containing variables LOSS, GDP, HPI and UE. (I have attached it in case it is required). Having renamed the variables as l,g,h and u, I wish to run a Lasso Regression with l as the dependent variable and all the other 3 as the independent variables. data=read.table("data.txt", header=T) l=data$LOSS h=data$HPI u=data$UE g=data$GDP matrix=data.frame(l,g,h,u)
2001 Sep 10
5
?? hmm ??
Hello again! thanks to all who helped with overlay plots - v. easy in the end. Anyway, another new(ba)bee type question - the gurus will cringe I'm sure! Q. simple R function mm <- function (u) { x <- u$GDP x m <- mean(x) m } When the function is called the vector "x" does not get printed from within the function, but the mean value "m" does, why? I
2017 May 20
2
[PATCH] drm: remove NULL pointer check for clk_disable_unprepare
After long term efforts of fixing non-common clock implementations, clk_disable() is a no-op for a NULL pointer input, and this is now tree-wide consistent. All clock consumers can safely call clk_disable(_unprepare) without NULL pointer check. Signed-off-by: Masahiro Yamada <yamada.masahiro at socionext.com> --- drivers/gpu/drm/etnaviv/etnaviv_gpu.c | 15 +++++----------
2011 Sep 21
1
Strucchange gbreakpoints
Hi, I am a new user to R. I am using strucchange to generate breakpoints: -------------------------------------------------------------------------------------- > res <- gbreakpoints(GDP.new ~ 1,data=a,h=2,breaks=5) > print(res) Optimal 6-segment partition for `lm' fit: Call: gbreakpoints(formula = GDP.new ~ 1, data = a, h = 2, breaks = 5) Breakpoints at observation number: