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compat20
2006 Sep 25
0
Sampling distribution of correlation estimations derived from robust MCD and MVE methods
...ere in each of 100000 epochs, I
a. construct a matrix from two vectors, each containing 40 numbers
randomly sampled from a normal distribution.
b. apply cov.mve and cov.mcd to the resulting matrix.
c. obtain the correlations in the subsets selected by cor.mve: e.g., if
the matrix is called cormat20.ans, I request:
current.mve20 <- round(cov.mve(cormat20.ans, cor=T)$cor[[2]] ,3)
At the end of the day, I have the sampling distribution for these
correlations [i.e., what correlations exist in the subsets that MVE and MCD
tend to pick up when sampling from normal distribution].
Here is my qu...
2006 Sep 25
0
[PlainText Attempt] Sampling distribution of correlation estimations derived from robust MCD and MVE methods
...ere in each of 100000 epochs, I
a. construct a matrix from two vectors, each containing 40 numbers
randomly sampled from a normal distribution.
b. apply cov.mve and cov.mcd to the resulting matrix.
c. obtain the correlations in the subsets selected by cor.mve: e.g., if
the matrix is called cormat20.ans, I request:
current.mve20 <- round(cov.mve(cormat20.ans, cor=T)$cor[[2]] ,3)
At the end of the day, I have the sampling distribution for these
correlations [i.e., what correlations exist in the subsets that MVE and MCD
tend to pick up when sampling from normal distribution].
Here is my qu...