omega_inv | R Documentation |
omega
functionThis function is the inverse of omega
function
omega_inv(
p0 = NULL,
p0_v1 = 0.5,
p0_v2 = p0_v1,
p00 = p0_v1 * p0_v2,
correlation = NA,
only.value = TRUE,
interval = c(-1, 1),
tolerance = 0.001,
nearPD = TRUE,
force.independence = TRUE,
...
)
p0 |
matrix of joint probabilities. Default is |
p0_v1 , p0_v2 |
probablity of no precipitatin occurrences for the v1 and v2 time series respectively. |
p00 |
probability of no precipitation occurrence in both v1 and v2 simultanously returned by |
correlation |
numerical value. DEfault is |
only.value |
logical value. If |
interval |
see |
tolerance |
tolerance (numeric) parameter used for comparisons with the extreme value of marginal probabilities. Default is 0.001. |
nearPD |
logical. If |
force.independence |
logical value. Default is |
... |
further arguments for |
value of expected correlation between the corresponding Gaussian-distributed variables (see x
input argument of omega
.
This function finds the zero of the omega_root
function by calling uniroot
.
If the argument p0
is not NULL
and is a matrix of joint probabilities, the function returns a correlation matrix by using the elements of p0
ass joint probabilities for each couple and p0_v1
as a vector of marginal probability of each occurrence/no-occurrence
(In this case if the length of p0_v1
does not correspond to the number of columns of p0
, the marginal probabilities are taken from the diagonal of p0
).
See the R code for major details.
Emanuele Cordano
normalCopula
,pcopula
,omega
(and reference URLs therein)
x <- omega_inv(p0_v1=0.5,p0_v2=0.5,p00=1.1*0.5*0.5)
omega(x,p0_v1=0.5,p0_v2=0.5)
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