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# Resources

# Failure reading Maxboot parameters dataset, Error G0125 Read past end of file

hi,

I ran a bootstrap using the `Maxboot` function (from the Maximum Likliehood application package) and save the parameters into a file let say bootparameter.

My question is , how can i see the parameters distribution or read that bootparameter file?

If I try to read it with the `loadd` function, I get the error:

error G0125:Read past end of file

## 4 Answers

You are wanting to view the bootstrapped parameter estimates that the `maxboot` function saves to a GAUSS dataset, correct? If so, they should be in a file with a `.dat` extension, such as `bootparameter.dat`. You can load the contents of a GAUSS dataset into a file with the `loadd` function like this:

```
p_boot = loadd("bootparameter");
```

If `bootparameter.dat` is not in your GAUSS current working directory, make sure to add the path, i.e.:

```
p_boot = loadd("C:\\gauss13\\myproj\\bootparameter");
```

You can produce a plot showing the distribution using the MaxDensity procedure that comes with Maxlik. The arguments are the dataset containing the bootstrapped coefficients, and a list of columns that you want to be displayed.

**> MAXdensity

**

** Purpose: To compute kernel density estimate and plot.

**

**

** Format: ( px,py,sm } = MAXdensity(dataset,pars);

**

** Input: dataset string, name of GAUSS dataset

** containing data.

**

** pars Kx1 vector, selected columns for

** estimation and display.

**

**

** Output: px _max_NumPointsx1 vector, abscissae.

** py _max_NumPointsx1 vector, ordinates.

** sm Kx1, or Nxk, or Nx1 smoothing coefficients.

**

** Remarks:

**

** kernel density plots of the selected parameters are

** generated.

**

** Globals:

**

** _max_Kernel Kx1 character vector, type of kernel:

**

** NORMAL - normal kernel

** EPAN - Epanechnikov kernel

** BIWGT - biweight kernel

** TRIANG - triangular kernel

** RECTANG - rectangular kernel

** TNORMAL - truncated normal kernel

**

** If _max_Kernel is scalar, the kernel is the same

** for all parameters. Default = { NORMAL };

**

** _max_NumPoints scalar, number of points to be computed for plots

**

** _max_EndPoints Kx2 matrix, lower (in first column) and upper

** (in second column) endpoints of density. Default is

** minimum and maximum, respectively, of the parameter

** values. If 1x2 matrix, endpoints will be the same

** for all parameters.

**

** _max_Smoothing Kx1 vector or Nx1 vector or NxK matrix, smoothing

** coefficients for each plot. If scalar, smoothing

** coefficient will be the same for each plot. If zero,

** smoothing coefficient will be computed by CMLdensity.

** If matrix, smoothing coefficient will be different for

** each observation.

** Default = 0;

**

** _max_Truncate Kx2 matrix, lower (in first column) and upper (in

** second column) truncation limits for truncated normal

** kernel. If 1x2 matrix, truncations limits will be the

** same for all plots. Default is minimum and maximum,

** respectively.

thank all of you. I have tried your suggestions but that the error message i keep receiving:

C:\gauss12\src\saveload.src(54) : error G0125 : Read past end of file

Currently active call: loadd [54] C:\gauss12\src\saveload.src

Stack trace:

loadd

I opened the dataset file that you sent in and checked the dimensions of the dataset like this:

open fh = eltcoeff for read; r = rowsf(fh); c = colsf(fh);

It reported that the dataset had 0 rows and 36 columns. I next checked to see what variables were in the dataset like this:

//using same 'fh' file handle from above vnames = getnamef(fh); print vnames;

and saw that the variable names:

PAR_1 PAR_2 PAR_3 . . . PAR_36

had been added to the dataset, but no values were assigned to them. It seems that a problem is occurring such that the data is not being written to the dataset.

## Your Answer

## 4 Answers

You are wanting to view the bootstrapped parameter estimates that the `maxboot` function saves to a GAUSS dataset, correct? If so, they should be in a file with a `.dat` extension, such as `bootparameter.dat`. You can load the contents of a GAUSS dataset into a file with the `loadd` function like this:

```
p_boot = loadd("bootparameter");
```

If `bootparameter.dat` is not in your GAUSS current working directory, make sure to add the path, i.e.:

```
p_boot = loadd("C:\\gauss13\\myproj\\bootparameter");
```

You can produce a plot showing the distribution using the MaxDensity procedure that comes with Maxlik. The arguments are the dataset containing the bootstrapped coefficients, and a list of columns that you want to be displayed.

**> MAXdensity

**

** Purpose: To compute kernel density estimate and plot.

**

**

** Format: ( px,py,sm } = MAXdensity(dataset,pars);

**

** Input: dataset string, name of GAUSS dataset

** containing data.

**

** pars Kx1 vector, selected columns for

** estimation and display.

**

**

** Output: px _max_NumPointsx1 vector, abscissae.

** py _max_NumPointsx1 vector, ordinates.

** sm Kx1, or Nxk, or Nx1 smoothing coefficients.

**

** Remarks:

**

** kernel density plots of the selected parameters are

** generated.

**

** Globals:

**

** _max_Kernel Kx1 character vector, type of kernel:

**

** NORMAL - normal kernel

** EPAN - Epanechnikov kernel

** BIWGT - biweight kernel

** TRIANG - triangular kernel

** RECTANG - rectangular kernel

** TNORMAL - truncated normal kernel

**

** If _max_Kernel is scalar, the kernel is the same

** for all parameters. Default = { NORMAL };

**

** _max_NumPoints scalar, number of points to be computed for plots

**

** _max_EndPoints Kx2 matrix, lower (in first column) and upper

** (in second column) endpoints of density. Default is

** minimum and maximum, respectively, of the parameter

** values. If 1x2 matrix, endpoints will be the same

** for all parameters.

**

** _max_Smoothing Kx1 vector or Nx1 vector or NxK matrix, smoothing

** coefficients for each plot. If scalar, smoothing

** coefficient will be the same for each plot. If zero,

** smoothing coefficient will be computed by CMLdensity.

** If matrix, smoothing coefficient will be different for

** each observation.

** Default = 0;

**

** _max_Truncate Kx2 matrix, lower (in first column) and upper (in

** second column) truncation limits for truncated normal

** kernel. If 1x2 matrix, truncations limits will be the

** same for all plots. Default is minimum and maximum,

** respectively.

thank all of you. I have tried your suggestions but that the error message i keep receiving:

C:\gauss12\src\saveload.src(54) : error G0125 : Read past end of file

Currently active call: loadd [54] C:\gauss12\src\saveload.src

Stack trace:

loadd

I opened the dataset file that you sent in and checked the dimensions of the dataset like this:

open fh = eltcoeff for read; r = rowsf(fh); c = colsf(fh);

It reported that the dataset had 0 rows and 36 columns. I next checked to see what variables were in the dataset like this:

//using same 'fh' file handle from above vnames = getnamef(fh); print vnames;

and saw that the variable names:

PAR_1 PAR_2 PAR_3 . . . PAR_36

had been added to the dataset, but no values were assigned to them. It seems that a problem is occurring such that the data is not being written to the dataset.