HT04_Lag | R Documentation |
Implements the version of the conditional multivariate approach of Heffernan and Tawn (2004) proposed in Keef et al. (2013) which incorporates lags between the variables. Function utilizes the mexDependence
and predict.mex.conditioned
functions from the texmex
package.
HT04_Lag(
data_Detrend_Dependence_df,
data_Detrend_Declustered_df,
Lags,
u_Dependence,
Migpd,
mu = 365.25,
N = 100,
Margins = "gumbel",
V = 10,
Maxit = 10000
)
data_Detrend_Dependence_df |
A data frame with (n+1) columns, containing in column
|
data_Detrend_Declustered_df |
A data frame with (n+1) columns, containing in column
|
u_Dependence |
Dependence quantile. Specifies the (sub-sample of) data to which the dependence model is fitted, that for which the conditioning variable exceeds the threshold associated with the prescribed quantile. Default is |
Migpd |
An |
Margins |
Character vector specifying the form of margins to which the data are transformed for carrying out dependence estimation. Default is |
V |
See documentation for |
Maxit |
See documentation for |
Lag |
Matrix specifying the lags. The no lag i.e. |
List comprising the fitted HT04 models Models
, proportion of the time each variable is most extreme, given at least one variable is extreme Prop
, residuals z
, as well as the simulated values on the transformed u.sim
and original x.sim scales.
Dataframe_Combine
Decluster
GPD_Fit
Migpd_Fit
HT04(data_Detrend_Dependence_df = S22.Detrend.df,
data_Detrend_Declustered_df = S22.Detrend.Declustered.df,
Migpd = S22_GPD, u_Dependence=0.7,Margins = "gumbel")
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