Properties
Private _distributions
Defined in ql/experimental/math/tcopulapolicy.ts:184
Private _latentVarsCumul
Defined in ql/experimental/math/tcopulapolicy.ts:186
Private _latentVarsInverters
Defined in ql/experimental/math/tcopulapolicy.ts:187
Private _varianceFactors _variance
Factors: Real [] = []
Defined in ql/experimental/math/tcopulapolicy.ts:185
Methods
allFactorCumulInverter
allFactorCumulInverter( probs: Real [] ) : Real []
Defined in ql/experimental/math/tcopulapolicy.ts:155
Parameters
Returns Real []
cumulativeY
Defined in ql/experimental/math/tcopulapolicy.ts:99
Parameters
cumulativeZ
Defined in ql/experimental/math/tcopulapolicy.ts:108
Parameters
density
Defined in ql/experimental/math/tcopulapolicy.ts:114
Parameters
getInitTraits
Defined in ql/experimental/math/tcopulapolicy.ts:86
Returns any
init
Defined in ql/experimental/math/tcopulapolicy.ts:27
Parameters
Default value factorWeights: Real [] [] = [[]]
Default value vals: initTraits = new TCopulaPolicy.initTraits()
inverseCumulativeDensity
Defined in ql/experimental/math/tcopulapolicy.ts:145
Parameters
inverseCumulativeY
Defined in ql/experimental/math/tcopulapolicy.ts:131
Parameters
inverseCumulativeZ
Defined in ql/experimental/math/tcopulapolicy.ts:140
Parameters
numFactors
Defined in ql/experimental/math/tcopulapolicy.ts:81
varianceFactors
varianceFactors( ) : Real []
Defined in ql/experimental/math/tcopulapolicy.ts:95
Returns Real []
Legend
Module Object literal Variable Function Function with type parameter Index signature Type alias Type alias with type parameter
Enumeration Enumeration member Property Method
Interface Interface with type parameter Constructor Property Method Index signature
Class Class with type parameter Constructor Property Method Accessor Index signature
Inherited constructor Inherited property Inherited method Inherited accessor
Protected property Protected method Protected accessor
Private property Private method Private accessor
Static property Static method
Student-T Latent Model's copula policy.
Describes the copula of a set of normalized Student-T independent random factors to be fed into the latent variable model. The latent model requires the independent variables to be of unit variance so the policy expects the factors coefficients to be as usual and the T variables to be normalized, the normalization is performed by the policy. To normalize the random variables they are divided by the square root of the variance of each T ($ \frac{\nu}{\nu-2}$)