similar to: how to make read-only data frames?

Hi R folk, I have a time series of scalar downstream velocity data measured across a tidal channel. The variables are the locations in bins across the channel, the samples are over time. The fluctuation over the tide cycle is an enormous fraction of the time variation in the data ... 96%. The spectral energy of the tide is concentrated in a couple bands that make up the major constituents of the

Hi, I have had a look around the forums and I can't seem to find anything that works with my data. I have lats, longs, time, tidal speed and direction and need to plot this in an xy plot to determine changes over time. contour and cloud have been recommended to me as a way to do this but I can't figure out how to get 5 dimensions into this. I want lat and long as my x and y, time as my

I am looking at using R to analyze time series data containing a tidal component. I need to remove the tidal signal to extract the time series of the phenomena I seek to study. A browse of R-project search engines has not been too fruitful? I've found 'hoa' and 'Rwave', but need further help getting started. THANKS. -wa

Trying to use rcmd in our Windows environment to launch tasks on remote servers. We are using the job scheduler from Tidal corporation. The problem is the return code that's coming back to the job scheduler,Tidal, is from the RCMD NOT from the tasks that it launched. We need to get the return code from the task that was launched via rcmd. Help Lou Zollo Production Control Manager

Hello R users, I am trying to use R to do the low pass filter analysis for the tidal data. I am a novice in R and so far been doing only simple stuffs on R. I found a package called signal but couldn't find the proper tutorial for the low pass filter. Could anyone point me to the proper tutorial or starting point on how to do low pass filter analysis in R ? Thank you so much. Janesh

dear Jim, Thanks for your reply and your proposition. I forgot to provide the header of the dataframe, here it is: ================================================================================ Byte-by-byte Description of file: lvg_table2.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations

You should be able to use that header information to create the correct parameters to the read_fwf function to read in the data. Jim Holtman Data Munger Guru What is the problem that you are trying to solve? Tell me what you want to do, not how you want to do it. On Thu, Oct 5, 2017 at 11:02 AM, jean-philippe <jeanphilippe.fontaine at gssi.infn.it> wrote: > dear Jim, > > Thanks

Dear all, Before I can get into serious Fourier analysis of Radon time-series I am practising with 24hour and 24.8hour sinusoids to assist with my interpretation of signals ittributed to tidal input to Radon time series. I am stuck. I have tried researching this to no avail. I am awating a book that should describe fourier transforms in detail and another one that should discuss the R

I'm doing these manipulations on the data frame and wondering why does R have to remember historical data on my operation and not just keep the needed info. Probably a basic fundamentals of the way R handles data .. Pls point me to the manual if possible .. I have this Index data: > head(NIFTY_INDX) Constituents.list.of.S.P.CNX.Nifty X X.1 X.2 X.3

Hi , I know this question has been asked twice in the past but to my knowldege, it still hasn't been solved. I am doing a zero inflated binomial model using the VGAM package, I need to obtain p values for my Tvalues in the vglm output. code is as follows > mod2=vglm(dmat~Season+Diel+Tidal.phase+Tidal.cycle,zibinomial, data=mp1) > summary(mod2) Call: vglm(formula = dmat ~ Season +

dear Jim, Yes I fixed the problem. Thanks again all of you for your contribution! This worked : start <- c(1, 20, 35, 41, 44, 48, 53, 59, 64, 70, 76, 78, 83, 88, + 93, 114, 122, 127) data1<-read_fwf("lvg_table2.txt",skip=70, fwf_widths(diff(start))) Well now I know how to deal with fixed-width files :) Cheers Jean-Philippe On 05/10/2017 18:42, jim

Hi, I am trying to plot the original data with the line of the model using the predict function. I want to add SE to the graph, but not sure how to get them out as the predict function for gls does not appear to allow for SE=TRUE argument. Here is my code so far: f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag) vf1Exp<-varExp(form=~hu3) B1D<-gls(f1,correlation=corGaus(form=Lat~Lon,

Hello, I write a commercial marine navigation and tidal current prediction application for Windows 3.1 (compiled with Borland c++ 3.1). I am considering releasing this or a variant of this under something like Linux. My goal is to continue to develop bells and whistles but to share the load with others. No particular commercial goals. In order to get recreational sailboat racers to use it I

Based on my reading of the release pages (https://gcc.gnu.org/releases.html and http://releases.llvm.org/) 6/5 would make GCC 4.7 and Clang 3.1 required, and GCC 4.8 and Clang 3.3 the first to not warn. 6/5 is surprisingly close to making the policy conform to exactly our current time-lag, where we are GCC4.8 (instead of 4.7) and Clang 3.1 (also 3.1). -Erich From: Andrew Kelley

I have a question concerning the Wilcoxon signed-rank test, and specifically, which R subroutine I should use for my particular dataset. There are three different commands in R (that I'm aware of) that calculate the Wilcoxon signed-rank test; wilcox.test, wilcox.exact, and wilcoxsign_test. When I run the three commands on the same dataset, I get different p-values. I'm hoping that

--- feeds/feed.xml | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/feeds/feed.xml b/feeds/feed.xml index 0d16cd9..2390cd0 100644 --- a/feeds/feed.xml +++ b/feeds/feed.xml @@ -7,6 +7,30 @@ <atom:link href="http://xiph.org/flac/feeds/feed.xml" rel="self" type="application/rss+xml" /> <item> + <title>FLAC

Here''s the full error: 1) Error: test_add_message_to_existing_ticket(TicketTest): ArgumentError: Unknown key(s): group /usr/lib/ruby/gems/1.8/gems/activesupport-1.2.4/lib/active_support/core_ext/hash/keys.rb:48:in `assert_valid_keys'' /usr/lib/ruby/gems/1.8/gems/acts_as_paranoid-0.2/lib/acts_as_paranoid.rb:125:in `validate_find_options''

This is an example of two months of data from a twenty four month data set that I would like to apply this too. These data are subsets of the same stations throught time, but differing ones were included on different sampling dates. I would like to subset these data and then put them together as a big matrix with the by column being RiverMile. What is the easiest way to proceed as this is a

I have a mixed model with a binomial response, four factor variables and one random factor. m1=glmer(nbhf.hour~Season+Diel+Tidal.phase+Tidal.cycle+(1|POD.ID),family=binomial,data =bl1,control=list(msVerbose=TRUE)) I have really need to try and find a post hoc test for this model and finding the pariwise comparisons, note the dataset is unbalanced. I had read many questions on this and there

Hi I have both host and KVM/QEMU guest VM running linux. Questions: What are the constituents of the virsh dump? - What all areas does it dumps? - Is it same as taking guest VM's core dump via kexec/kdump? - Does it include QEMU's info to debug qemu-level issues? Thanks much in advance. >harish -------------- next part -------------- An HTML attachment was scrubbed... URL: