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rmarkov

Markov Switching Model MSwM with more than 2 states

Has anyone tried running Markov Switching Model with 'MSwM' and setting more than 2 regimes? With three it does not seem to work

Data (r_t)

[1]  0.0000000000 -0.0101170400 -0.0016032060 -0.0071256520  0.0007075710 -0.0021212120  0.0021257210 -0.0013131310 -0.0003034290 -0.0014164310  0.0026342450  0.0014147130
[13]  0.0039354190 -0.0019097400 -0.0018126890 -0.0015133170 -0.0059614020 -0.0055905670  0.0049064700 -0.0009663310  0.0000509087 -0.0146609650  0.0007232900 -0.0010325250
[25]  0.0043410850 -0.0027271790  0.0031474120  0.0004114800 -0.0002056560 -0.0016455830  0.0044297930 -0.0138461540  0.0017680710  0.0021802330 -0.0063203150 -0.0039605960
[37] -0.0036633870 -0.0042021220  0.0033231350 -0.0078334470 -0.0027554050 -0.0010626990 -0.0079787230 -0.0007506700 -0.0004561060  0.0008857870 -0.0026818280 -0.0034419710
[49]  0.0012951970 -0.0012935220 -0.0024284940 -0.0154179060  0.0032967030  0.0029572840  0.0160532930  0.0049441100  0.0033689840 -0.0026115230  0.0023511810  0.0021324230
[61] -0.0034046180  0.0002135160  0.0001601020  0.0020809990 -0.0115015970 -0.0068950660  0.0070514210 -0.0066788750 -0.0012471530  0.0017916280 -0.0028181230  0.0039130430
[73]  0.0015158080  0.0000000000  0.0023243240 -0.0023189340  0.0019459460 -0.0002157960 -0.0014569390 -0.0056741420  0.0054347830 -0.0054054050  0.0010869570  0.0014115090
[85]  0.0018432180 -0.0064935060  0.0032679740  0.0043431050 -0.0008648650 -0.0011902190  0.0021666130 -0.0055129180  0.0000000000  0.0000000000 -0.0367391300 -0.0230196340
[97] -0.0600600600  0.0788891620  0.0127562640 -0.0008996850

Code

model=glm(r_t ~ 1)
mod = msmFit(model, k = 3, p = 1, sw = rep(TRUE, 3))

Error message

Error in std[i] = summary(mod1)$sigma : replacement has length zero
Solution

  • This has nothing to do with the number of states. msmFit(model, k = 2, p = 1, sw = rep(TRUE, 3)) does not work either.

    The problem here is that the wrong method for msmFit is used. Instead of the method for glm, the method for lm objects is used because class(model) is c("glm", "lm").

    The easiest way to fix your problem is to use lm instead of glm.

    Alternatively, if you prefer the glm method, you can explicitly call it: 

    msmFit.glm <- selectMethod(msmFit, c("glm","numeric","logical","ANY","missing","ANY"))
mod = msmFit.glm(model, k = 3, p = 1, sw = rep(TRUE, 2))

    NOTE that the glm and the lm methods are very different! See ?"MSM.lm-class" and ?"MSM.glm-class" for more details.