similar to: tsdiag() titles

This question will probably get me in trouble on theoretical grounds, but I will pose it anyway. The situation: I recently ran a field study looking for differences in sugarbeet cultivar tolerance to a specific herbicide. The study was set up so that 37 cultivars were treated with 4 different applications of the herbicide (37*4 factorial). In doing so, we found that the interaction effect was

You need to give the model formula that gave your output. There are two sources of variation (at least), within and between locations; though it looks as though your analysis may have tried to account for this (but if so, the terms are not laid out in a way that makes for ready interpretation. The design is such (two locations) that you do not have much of a check that effects are consistent over

I've tried several different ways to accomplish this, but as yet to no avail. My y-axis for a plot has a rather long label, and thus I have been using "/n" to break it into two lines. However, to make it technically correct for publication, I also need to use superscript in the label. For example: par(oma=c(0,0,2,0),mar=c(5,6,0.25,2),lheight=1) plot(1:10,

Hello, I'm getting the following error message when I try to run 'tsdiag' on what seems to be a valid time series: > tsdiag(small) returns: [Error in tsdiag(small) : no applicable method for "tsdiag"] where small is a little test series where I have isolated this problem (the original has 30-years worth of daily data) When I print it (small), it looks like the

HI list, I want to know whether tsdiag uses k-(p+q) as the lag in ljung box test. How is it possible to save those values nuncio -- Nuncio.M Research Scientist National Center for Antarctic and Ocean research Head land Sada Vasco da Gamma Goa-403804 [[alternative HTML version deleted]]

The "tsdiag" function in the TSA package overrides the "tsdiag" function in the "stats" package. There are a few annoying bugs in the TSA's version of the function so I would like to use the "stats" function but still have access to other TSA functions. I have tried using stats::tsdiag( ) but as long as the TSA package is attached the function from

Hi R-Helpers, I'm dealing with the STL procedure and trying to apply the tsdiag and StructTS onto the ts object to analyse the different parameters which need to be set. How can I use the tsStructure & tsdiag to create a seasonal, trend and cycle subseries plot so that I can select & analyse the correct np,ns, nt and nl? The problem is that too much signal goes into the seasonal

Dear Everyone, The document of `tsdiag? says > These tests are sometimes applied to the residuals from an ARMA(p, q) fit, in which case the references suggest a better approximation to the null-hypothesis distribution is obtained by setting fitdf = p+q, provided of course that lag > fitdf. This implies that we should pass the `fitdf' parameter when applying `Box.test' to

Hi all, I am modelling a time series with missing data. *Q1)* However, I am not sure if I should use the next *graphics* to understand my data: *a)* ACF & PACF (original series) *b)* ACF & PACF (residuals) * * *Q2)* I am using *tsdiag*, so I obtain a graphic with 3 plots: stand. residuals vs time; acf for residuals; Ljung-Box for residuals (it is wrong for residuals). I know that using

Hi, I am newbie user of ggplot and would like some assistance in implementing time series plots. I'd like to know how the tsdiag plot can be made in ggplot? Thanks Harsh Singhal Decisions Systems, Mu Sigma Inc.

Greetings R-helpers, I am attempting to fit an lme() while specifying a correlation structure, but I'm getting into trouble long before I get to that point. I am receiving the error: Error in y[revOrder] - Fitted : non-conformable arrays It doesn't seem to matter how simple or complex the model I specify is, it always gives this same error message. This makes me suspect something is

I've just built R 2.9.2 from source on Slackware Linux 13.0 - 32-bit (will try 64-bit also next) - and seen: > Collecting examples for package 'stats' > Running examples in package 'stats' > Error: testing 'stats' failed > Execution halted > make[3]: *** [test-Examples-Base] Error 1 Looking at R-2.9.2/tests/Examples/stats-Ex.Rout.fail I see: ... >

Hi R experts, I am trying to remove autocorrelation from Simple Moving Average time series. I know that this can be done by using seasonal ARIMA like, library(TTR) data <- rnorm(252) n=21 sma_data=SMA(data,n) sma_data=sma_data[-1:-n] acf(sma_data,length(sma_data))

On Wed, Aug 9, 2017 at 12:14 PM, Noralf Trønnes <noralf at tronnes.org> wrote: > > Den 09.08.2017 01.42, skrev Joe Kniss: >> >> Because all drivers currently use gem objects for framebuffer planes, >> the virtual create_handle() is not required. This change adds a >> struct drm_gem_object *gems[4] field to drm_framebuffer and removes >> create_handle()

On Wed, Aug 9, 2017 at 12:14 PM, Noralf Trønnes <noralf at tronnes.org> wrote: > > Den 09.08.2017 01.42, skrev Joe Kniss: >> >> Because all drivers currently use gem objects for framebuffer planes, >> the virtual create_handle() is not required. This change adds a >> struct drm_gem_object *gems[4] field to drm_framebuffer and removes >> create_handle()

On Wed, Aug 9, 2017 at 12:14 PM, Noralf Trønnes <noralf at tronnes.org> wrote: > > Den 09.08.2017 01.42, skrev Joe Kniss: >> >> Because all drivers currently use gem objects for framebuffer planes, >> the virtual create_handle() is not required. This change adds a >> struct drm_gem_object *gems[4] field to drm_framebuffer and removes >> create_handle()

Has anyone written any code for the Hodrick-Prescott filter? I have a some uncompiled FORTRAN code from Ed Prescott but I'd like to save myself some programming time if possible. Thanks for your help. Nick Davis Crown Financial Policy Asset and Liability Management Branch The New Zealand Treasury Direct: +64-4-471-5924 Fax: +64-4-499-0143 Email:

i am using sarima() function as below ___________________________________________________________________________________________ sarima=function(data,p,d,q,P=0,D=0,Q=0,S=-1,tol=.001){ n=length(data) constant=1:n xmean=matrix(1,n,1) if (d>0 & D>0) fitit=arima(data, order=c(p,d,q), seasonal=list(order=c(P,D,Q), period=S),

I've had a play with this and, due to my own short-comings, remain none the wiser. In particular, I'm not sure what value of 'spar' is consistent with the magic lambda=1/1600 for quarterly data. I initially interpreted spar as lambda and tried setting spar=1/1600. This results in almost no smoothing while spar=1600 causes an error. The smooth.spline function seems to want

Hi have been trying to get winbind working on Solaris 9 but to no effect. version info: samba: 3.0.0 openldap: 2.1.23 kerberos: MIT 1.3.1 Have followed the instructions in every howto, usenet posting I could find: nscd not running created relevant links in /lib and /lib/security/sparcv9 applied patch for nsswitch as recommended kinit -e works net ads join works wbinfo -t works wbinfo -u