Displaying 4 results from an estimated 4 matches for "correspnd".
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correspond
2005 Aug 08
3
Reg. getting codewords from codelengths
...l take the example of an actual codebook that i found in a valid
vorbis encoded file as shown below.
[SK] +------Codebook [0] --------
[SK] Codebook Dimensions = 1
[SK] Codebook Entries = 8
[SK] Unordered
[SK] 1, 6, 3, 7, 2, 5, 4, 7,
[SK] NO Mapping
[SK] +------Codebook [1] --------
What are the correspnding codewords? I have written below a few, but I
think they might be wrong.
---------------------------
Entry len | Codeword |
---------------------------
1 | 0
6 | 100000
3 | 000
7 | 10000000
2 |
5 |
4 |
7 |...
2008 Sep 22
1
SmoothScatter plot range issue
...rea but the perspective is a bit skewed. I
would like to standardize these plots to a uniform window size that does not
depend on the range of values in the dataframe. However, when I resize the
plot using xlim or ylim, there is a light blue background that surrounds the
immediate area of the data (correspnding to the range of the points listed
in the dataframe), surrounded by extra white space for the new xlim and ylim
values I have added. Some of the rings around the datapoints are also cut
off at the margins.
I would like to stop the plot from being cut off, and want this light blue
"range&quo...
2012 Jan 31
0
Using 2SLS to mimic SEM with nested data
...it doesn't seem like extending the 2SLS approach should be too difficult. One of my uncertainties though is how to assess model fit. For example, one of the rules of thumb I learned is that the R2 from all first stage regressions should be at least .10. It's not clear to me though what the correspnding criterion would be if I were running a mixed model.
I also used a Basman F-statistic to assess model fit when a did a 2SLS. I no longer rember the details of its calculation, but wonder if it translates well to mixed models (or if there are other fit statistics that do).
If anyone has knowledg...
2012 May 27
7
Customized R Regression Output?
Hello R-Experts,
I am facing the problem that I have to estimate several parameters for a lot
of different dependent variables.
One single regression looks something like this:
y = beta0 + beta1 * x1 + beta2 * x2 + beta3 * x1 * x2 + beta4 * x4 + beta5 *
lag(x4,-1)
where y is the dependent variable and xi are the independent ones. Important
to me are the different estimates of betai and their