search for: vessell

Dear R users, I am querying an Oracle database using sqlQuery() from the RODBC package. What I would like to do is embed my R Sql query in a for loop. For example suppose the data.frame "vessel" contains two columns: vessel[,1]= vessel id and vessel[,2]=permit year I am using "vessel" as an input in a SQL based function that require inputs of permit year and vessel id

Hello, I want to select same data of a data frame that has information of fish catches: catch, vessel, trip, day, month, year where trip is the fishing operation number done in each day by each vessel, i.e. for each day, any vesel can have several register of catch corresponding to each operation. >From this data frame I want to do: 1. Add the catches of all trip by vessel and day; then

Hi professors I'm finding the best package in R for manage a big database about vessels. I need to divided the travel of each boat into tracks. I have GPS points. I would join these points in a line on the map. I make that with the function "lines", but I can't divided by vessel or by track, I saw several packages, for tracking animals but they had specifically variables. And I

Hi, I'm trying to create a plot showing the density distribution of some shipping data. I like the look of violin plots, but my data is not continuous but rather binned and I want to make sure its binned nature (not smooth) is apparent in the final plot. So for example, I have the number of individuals per vessel, but rather than having the actual number of individuals I have data in the

Hi -I am using R v 2.13.0. I am trying to use the aggregate function to calculate the percent at length for each Trip_id and CommonName. Here is a small subset of the data. Trip_id Vessel CommonName Length Count 1 230 Sunlight Shad,American 19 1 2 230 Sunlight Shad,American 20 1 3 230 Sunlight Shad,American 21

Han-Lin I don't think I have seen a reply so I will suggest that maybe you could try a different approach than what you are thinking about doing. I believe the current best practice is to use the weights as a covariate in a regression model - and bytheway - the weights are the inverse of the probabilities of selection - not the probabilities. Fundamentally, there is a difficulty in making

Hello, When I run the following glm model: modelresult=glm(CID~WS+SS+DV+DS, data=kimu, family=binomial) I get the following warning messages: 1: glm.fit: algorithm did not converge 2: glm.fit: fitted probabilities numerically 0 or 1 occurred What I am trying to do is model my response variable (CID: correct bird identification) as a function of the predictor variables weather state (WS), sea

I'm trying to do a Hosmer-Lemeshow 'goodness of fit' test on my logistic regression model. I found some code here: http://sas-and-r.blogspot.com/2010/09/example-87-hosmer-and-lemeshow-goodness.html The R code is above is a little complicated for me but I'm having trouble with my answer: Hosmer-Lemeshow: p=0.6163585 le Cessie and Houwelingen test (Design library): p=0.2843620

I am attempting to fit discrete data (daily counts of arrivals of recreational vessels at locks on a river) using the fit.dist package. Some distributions return values of NaN and Inf for certain situations, an example with Inf values is shown below. # of vessels: 1 2 3 4 5 6 7 8 9 10 11 # of days with # of vessels: 35 20 10 5 6

Hi, All Thanks to Robert Baskin, Thomas Lumley, and Spencer Graves for the valuable helps. I have learned a lot from this discussion. I put all discussions together without editing, so we can see how things are evolved. Likely, I have a lot of articles to read. As in the discussion, mixed modeling approach is a poosible but may be over-kill in my posted data analyses. I will explore other

Hello everyone, I was trying to fit an arima model to a daily historical data, but, for some reason, havent been able to. I basically have 212 observations (from 12/1/2012 to 06/30/2013) containing the number of transits for a particular vessel. The following messages are produced by R: dailytrans.fit<-arima(dailytrans$transits, order=c(0,1,2), seasonal=list(order=c(0,1,2), period=365),

Hi, I am extracting positions data from the marine traffic website. The table has a "Timestamp" column which, in the browser, appears with the format yyyy-mm-dd HH:MM (UTC), e.g. 2017-07-10 14:04 (UTC). When I import the table, the same date "2017-07-10 14:04 (UTC)" appears as "1499696500149969650021 minutes ago", This is the more recent date and time. Older

I am wondering if anyone knows how to use predict with a glmmPQL model, where you want to predict the response for one factor in the model? Originally I used predict on a GLM (gamma, log link) in the following way: p.1<-predict(model1,data.frame(year=as.factor(xv),nafdiv=as.factor(rep(" 3N",length(xv))), duration=1000, cfv=as.factor(rep(106166,length(xv))),

...survey is only done once, so if there are 2 ships (or more), the number of animals (and all other survey-related info) is just copied over on another line df <- data.frame(Survey = c(1, 1, 2, 3), NAnimals = c(10, 10, 1, 0), Vessel = c("A", "B", "C", "D"), VesselLength = c(20, 50, 40, 70), VesselSpeed = c(10, 5, 4, 5), Direction = c("West", "East", "West", "West")) Disclaimer: this is a crosspost from here ( https://stats.stackexchange.com/questions/318667/multiple-instances-of-predictor-variables ). Many thanks. [...

Is there an optimal / minimum sample size for attempting to construct a classification tree using /rpart/? I have 27 seagrass disturbance sites (boat groundings) that have been monitored for a number of years. The monitoring protocol for each site is identical. From the monitoring data, I am able to determine the level of recovery that each site has experienced. Recovery is our

R-help, Sorry for posting again the same question (dated 26-03-2007) but all my mails have been sent to the recycle bin without possibility of recovering and thus I don't know if anyone has answer my query. Here is the original message: I'm applying a gam model (package mgcv) to predict relative abundances of a fish species. The covariates are year, month, vessel and statistical

Dear R-helper, I wonder if anyone can help me. I am trying to convert a dataset to a format recognizable by a software onboard a research vessel but I am having problems with some steps. I have a data frame as follows: Conc Lat Lon Depth Point0000 56.25 -5.65 70 Point0001 56.55 -5.35 85 Point0002 56.25 -5.65 65 Point0003 56.37

Dear R Help, I would like to use the glmer.nb function for mixed modelling using negative binomial distribution please. On the CRAN website apparently this function is called from the lme4 package (version 0.99999911-1). I have downloaded the latest version of the lme4 package (version 0.999999-2) and have recently reinstalled the latest version of 64-bit R (version 3.0.1) but after

Hi Andrey, 2015-04-19 0:12 GMT+02:00 Andrey Repin <anrdaemon at yandex.ru>: > Greetings, Davor Vusir! > >>> Hi, there are two separate points of view here, map 'Administrator' to the >>> 'root' user, or give 'Administrator' a uidNumber. If you do the first then >>> 'Administrator' can change directory settings on a Unix

Dear Jeff, I am sorry, I didn't notice that it was not plain text. I hope that it is now in the correct format. I explain the problem again, now with more detais. I am collecting the track positions of our research vessel from www.marinetraffic.com. In the page, the data appear in a table: Timestamp Source Speed (kn) Latitude (?) Longitude (?) Course (?) Show on Map