A suite of functions for finance, including the estimation of variance matrices via a statistical factor model or Ledoit-Wolf shrinkage.

Changes in version 1.02 (2014-03-09)

NEW FEATURES

```
o The 'slideWeight' function is added. This creates a vector
suitable to use as time weights -- for example, the 'weights'
argument to 'var.shrink.eqcor' or 'factor.model.stat'.
```

NON-BACKWARD COMPATIBLE

```
o if in 'factor.model.stat' the 'constant.returns.okay'
argument is 'TRUE', then any columns with constant values
now get a variance of zero rather than the default variance
for an all missing column. The previous behavior could
arguably be considered a bug.
```

CHANGES

```
o the default value of 'tol' in 'var.shrink.eqcor' is now
1e-4 instead of 1e-3. This is still a guess, but it seems
to be a better guess.
o equal time weights can be specified with 'weight=NULL'
in 'factor.model.stat' and 'var.shrink.eqcor'.
o 'cumulative.variance.fraction' is a new component of the result of
'factor.model.stat' when its output is the factor model.
o 'constant.names' is a new component of the result of
'factor.model.stat' when its output is the factor model.
```

BUG FIXES

```
o The 'x' in 'factor.model.stat' is immediately coerced with
'as.matrix' to avoid subsetting problems with some data types,
'timeSeries' for instance.
o A second attempt is made with 'svd' inside 'factor.model.stat'
if the first attempt fails to converge.
It also does a sanity check on the result of 'svd'.
```

Changes in version 1.01 (2012-02-12):

NEW FEATURES

```
o The 'threeDarr' function is added. This creates three-dimensional
arrays out of matrices.
```

CHANGES

```
o 'var.shrink.eqcor' and 'factor.model.stat' have a new argument
'verbose' that controls whether some warnings are given. Both
functions can warn if there are no negative values in the input
'x' -- an indication in finance that prices rather than returns
are given. Warnings in 'factor.model.stat' about constant
columns in 'x' and negative specific variances are also controlled.
o 'var.add.benchmark' has a new argument 'sum.to.one' that allows
a "benchmark" to have weights that sum to something other than
one. An example is to give portfolio weights minus benchmark
weights.
```

BUG FIXES

```
o (none)
```