newintern - 1 month ago 5

R Question

I have installed the mixdist package in R to combine distributions. Specifically, I'm using the

`mix()`

Basically, I'm getting

`Error in nlm(mixlike, lmixdat = mixdat, lmixpar = fitpar, ldist = dist, : `

missing value in parameter

I googled the error message, but no useful results popped up.

My first argument to

`mix()`

`data.df <- as.mixdata(data.df)`

My second argument has two rows. It is a data frame called datapar, formatted exactly like pikepar. My

`pi`

`mu`

`sigma`

My call to

`mix()`

`fitdata <- mix(data.df, datapar, "norm", constr = mixconstr(consigma="CCV"), emsteps = 3, print.level = 2)`

The printing shows that my

`pi`

I would appreciate any help in sorting out this error.

Thanks,

n.i.

Answer

Using the test data you linked to

```
library(mixdist)
time <- seq(673,723)
counts <-c(3,12,8,12,18,24,39,48,64,88,101,132,198,253,331,
419,563,781,1134,1423,1842,2505,374,6099,9343,13009,
15097,13712,9969,6785,4742,3626,3794,4737,5494,5656,4806,
3474,2165,1290,799,431,213,137,66,57,41,35,27,27,27)
data.df <- data.frame(time=time, counts=counts)
```

We can see that

```
startparam <- mixparam(c(699,707),1 )
data.fit <- mix(data.mix, startparam, "norm")
```

Gives the same error. This error appears to be closely tied to the data (so the reason this data does not work could be potentially different than why yours does not work but this is the only example you offered up).

The problem with this data is that the probability between the two groups becomes indistinguishable at some point. Then that happens, the "E" step of the algorithm cannot estimate the `pi`

variable properly. Here

```
pnorm(717,707,1)
# [1] 1
pnorm(717,699,1)
# [1] 1
```

both are exactly 1 and this seems to be causing the error. When `mix`

takes 1 minus this value and compares the ratio to estimate group, it gets `NaN`

values which are propagated to the estimate of proportions. When internally these `NaN`

values are passed to `nlm()`

to do the estimation, you get the error message

```
Error in nlm(mixlike, lmixdat = mixdat, lmixpar = fitpar, ldist = dist, :
missing value in parameter
```

The same error message can be replicated with

```
f <- function(x) sum((x-1:length(x))^2)
nlm(f, c(10,10))
nlm(f, c(10,NaN)) #error
```

So it appears the `maxdist`

package will not work in this scenario. You may wish to contact the package maintainer to see if they are aware of the problem. In the meantime you will will need to find another way to estimate the parameters of you mixture model.