[R] depmixs4 standardError() issue

2023-05-31 Thread Heather Lucas
Hello, I've been enjoying using the "Mixture and Hidden Markov Models in R" by Visser & Speekenbrink to learn how to apply these analyses to my own data using depmixS4. I currently have a fitted 4-state mixture model with three emissions variables and one binomial covariate (HS). I am trying

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Eric Berger
I sent you an updated response to deal with the redundant copies of the x-axis. Re-sending. par(mfrow=c(3,1)) plot(DAX.[, 1], log='y', ylab='DAX', xaxt="n") plot(DAX.[, 2], ylab='vel (%)', xaxt="n") plot(DAX.[, 3], ylab='accel (%)') On Wed, May 31, 2023 at 4:27 PM Spencer Graves wrote: > > > >

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Spencer Graves
On 5/30/23 10:23 AM, Eric Berger wrote: What if you just precede these commands as follows: par(mfrow=c(3,1)) plot(DAX.[, 1], log='y', ylab='DAX') plot(DAX.[, 2], ylab='vel (%)') plot(DAX.[, 3], ylab='accel (%)') Most of the space is consumed with two extraneous copies of the axis. We

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Eric Berger
Slight modification to have the xaxt ticks and labels only appear on the bottom chart par(mfrow=c(3,1)) plot(DAX.[, 1], log='y', ylab='DAX', xaxt="n") plot(DAX.[, 2], ylab='vel (%)', xaxt="n") plot(DAX.[, 3], ylab='accel (%)') On Tue, May 30, 2023 at 6:23 PM Eric Berger wrote: > > What if you

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Viechtbauer, Wolfgang (NP)
How about using the same 'mar' for all plots, but adding an outer margin? DAX <- EuStockMarkets[, 'DAX'] DAX. <- cbind(DAX, diff(log(DAX)), diff(diff(log(DAX colnames(DAX.) <- c("DAX", 'vel (%)', 'accel (%)') head(DAX.) par(mfrow=c(3,1), mar=c(1,4.5,0,2), oma=c(3,0,1,0)) plot(DAX.[, 1],

Re: [R] lattice xyplot: how to change the y-axis labels size using yscale.components.subticks on the right side and how to adapt the ticks number

2023-05-31 Thread Laurent Rhelp
I will try to explain in a bit more detail. 1. I want to have the labels on the right with a small size to be able to read them 2. I would like not to have the labels on the left 3.  I would like to be able to choose the number of principal ticks for every sensor. That is to say the value of

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Spencer Graves
On 5/31/23 9:20 AM, Eric Berger wrote: I sent you an updated response to deal with the redundant copies of the x-axis. Re-sending. par(mfrow=c(3,1)) plot(DAX.[, 1], log='y', ylab='DAX', xaxt="n") plot(DAX.[, 2], ylab='vel (%)', xaxt="n") plot(DAX.[, 3], ylab='accel (%)') I got that.

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Spencer Graves
On 5/31/23 2:12 PM, Viechtbauer, Wolfgang (NP) wrote: How about using the same 'mar' for all plots, but adding an outer margin? DAX <- EuStockMarkets[, 'DAX'] DAX. <- cbind(DAX, diff(log(DAX)), diff(diff(log(DAX colnames(DAX.) <- c("DAX", 'vel (%)', 'accel (%)') head(DAX.)

Re: [R] plot level, velocity, acceleration with one x axis

2023-05-31 Thread Deepayan Sarkar
I think your proposal of modifying plot.ts() to allow 'log' to be vectorized would be the most natural solution here. For what it's worth, the details of the implementation and the fact that you can supply a panel function allows an ugly hack: pfun <- function(...) { e <- parent.frame()

[R] Help sourcing datasets (.csv)

2023-05-31 Thread james carrigan
Dear Sir or Madam I’m trying to compile a collection of datasets that require use of the following hypothesis tests. Are there datasets within the R library that I can get access to? Kind regards James Carrigan Hypothesis Testing t.test(X,Y) — performs a two sample t-test between X and Y

[R] error in arfima...

2023-05-31 Thread akshay kulkarni
dear members, I am using arfima() from forecast package to model a time series. The following is the code: > LYGH[[202]] [1] 45.40 3.25 6.50 2.15 > arfima(LYGH[[202]]) Error in .fdcov(x, fdf$d, h, nar = nar, nma = nma, hess = hess, fdf.work = fdf$w) : NA/NaN/Inf

Re: [R-es] ayuda sobre grafico de barras simple

2023-05-31 Thread Proyecto R-UCA
Buenas, José: En una lista de software libre es preferible no usar formatos privativos de archivos como los que utiliza Microsoft. Las instrucciones siguientes hacen un gráfico de barras: x <- rbinom(10, 20, .3) barplot(table(x)) ¿Los valores no se corresponden con una variable cuantitativa

[R-es] ayuda sobre grafico de barras simple

2023-05-31 Thread Jose Betancourt Bethencourt
Estimados mi pregunta viene en archivo adjunto saludos José R pregunta.docx Description: MS-Word 2007 document ___ R-help-es mailing list R-help-es@r-project.org https://stat.ethz.ch/mailman/listinfo/r-help-es

Re: [R-es] ayuda sobre grafico de barras simple

2023-05-31 Thread Jose Betancourt Bethencourt
Gracias!! El 31/5/23, Javier Marcuzzi escribió: > Estimados > > José envio un archivo, pero no es privativo. Hay varios programas para > abrir un documento word, pero, dicho de otra forma, es docx, especificado > en: > > https://es.wikipedia.org/wiki/Office_Open_XML > > Bajo esas

[R-es] scale_colour_viridis en ggplot2

2023-05-31 Thread Javier Gómez Gonzalez
Hola a todos: Alguién me podría explicar cuales son las diferencias entre las diferentes escalas de viridis en ggplot2, es decir en qué se diferencian scale-colour_viridis_d de scale_colour_viridis_c, scale_colour_viridis_b. Y cual es la diferencia entre scale-fiil-viridis_d de

Re: [R-es] scale_colour_viridis en ggplot2

2023-05-31 Thread Manuel Spínola
Hola Javier, d = discrete c = continuous b = binary Manuel On Wed, 31 May 2023 at 14:51 Javier Gómez Gonzalez wrote: > Hola a todos: > > Alguién me podría explicar cuales son las diferencias entre las diferentes > escalas de viridis en ggplot2, es decir en qué se diferencian >

Re: [R-es] scale_colour_viridis en ggplot2

2023-05-31 Thread MAURICIO MARDONES
De acuerdo a Bard; • scale_colour_viridis_d: Esta función utiliza la paleta de colores "viridis" en una escala continua, donde los colores varían de forma suave y continua. Es adecuada para representar datos en los que se desea resaltar las variaciones sutiles en los valores de la