Multivariate modelling using VAR(p) and SVAR(p) different estimation methods, simulation, daily rainfall simulated series correction and deseasonalization are performed
mlpm(x, p, prob, nsim, smean, svar, fre = 365, outer = 0,plot = F,
rain = T, over = T, estimate = "ols", CCFlag = 20, Plag = 20, lsign = 0.05, des = T)
List of estimated coefficients matrix
List of estimated standard deviations coefficients matrix. Only for OLS and EGLS method
List of 'structure' of SVAR(p) model (1 define position of estimated parameter). Only for EGLS method
Residual series
Output List of ar function
Akaike Information Criterion index
Portmonteau statistic
List of simulated series
Multivariate series
Model order
Condifidence interval used to fix parameters in SVAR(p) model
Number of series to simulated
Mean and Variance smoothing windows of STL modified method
Series frequency. Default fre = 365
Outer loops of STL modified method. Default outer = 0
Logical variable: T to receive some graphics. Default plot = F
Logical variable: T to apply rain adaptor to simulated series. Default rain = F
Logical variable: T to use SVAR(p) model estimated with EGLS method. Need estimate = 'ols' Default over = T
Define VAR(p) estimation method. 'ols', 'burg', 'yw' (Yule-Walker). Default estimate = 'ols'
Lag of (Partial) Auto-CrossCorrelation function graphics . Default CCFlag = 20
Maximum lag of A-CCF used in the Portmanteau Test. Default Plag = 20
Portmanteau Test significance level. Default lsign = 0.05
Logical variable: T to remove seasonal components
Corrado Tallerini
Need integer periodical datasets. Simulation use Lutkepohl algorithm with a residuals vectorial permutation to obtain innovations. Parameters selections of EGLS method is defined by t-ratio approach.
Grimaldi S., Tallerini C., Serinaldi F. (2004) 'Modelli multivariati lineari per la generazione di serie di precipitazioni giornaliere' Giornata di Studio: Metodi Statistici e Matematici per l'Analisi Idrologiche Napoli 2004
Grimaldi S. , Serinaldi F. & Tallerini C. (2004) 'Multivariate linear parametric models applied to daily rainfall time series' Mediterranean Storms, 6rd EGU Plinius Conference held in Mediterranean Sea, Italy, October 2004
Lutkepohl, H. (1993) Introduction to Multiple Time Series Analysis 2nd edition, Springer-Verlag, Berlin.
Grimaldi, S., 'Linear parametric models applied on daily hydrological series', Journal of Hydrologic Engineering, Vol. 9, No 5 , September 2004.
Brockwell, P.J and Davis, R.A. (1990) Time Series: Theory and Methods 2nd edition, Springer, NY.
Hipel, K.W. and McLeod, A.I., (1994) Time Series Modelling of Water Resources and Enviromental Systems, Reading, UK.
Hosking, J.R.M. (1980) 'The Multivariate Portmanteau Statistic' Journal of the American Statistical Association, Vol.75, N.371, 502-608.
lpm, ar.egls, rain.adapt
##-- Mrain=mlpm(series.rainfall,3,0.95,0,120,120)
##-- Apply a SVAR(3) model with selection probability 95 % to series.rainfall
##-- after preventive deseasonalization with smoothing 120.
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