Gaussian estimation of first order time series models with Bernoulli observations

Bernoulli matrix approach for matrix differential models of first-order

The current paper contributes a novel framework for solving a class of linear matrix differential equations. To do so, the operational matrix of the derivative based on the shifted Bernoulli polynomials together with the collocation method are exploited to reduce the main problem to system of linear matrix equations. An error estimation of presented method is provided. Numerical experiments are...

Autoregressive Gaussian Random Vectors of First Order

bernoulli matrix approach for matrix differential models of first-order

the current paper contributes a novel framework for solving a class of linear matrix differential equations. to do so, the operational matrix of the derivative based on the shifted bernoulli polynomials together with the collocation method are exploited to reduce the main problem to system of linear matrix equations. an error estimation of presented method is provided. numerical experiments are...

Modified Maximum Likelihood Estimation in First-Order Autoregressive Moving Average Models with some Non-Normal Residuals

When modeling time series data using autoregressive-moving average processes, it is a common practice to presume that the residuals are normally distributed. However, sometimes we encounter non-normal residuals and asymmetry of data marginal distribution. Despite widespread use of pure autoregressive processes for modeling non-normal time series, the autoregressive-moving average models have le...

Tidal prediction using time series analysis of Buoy observations

Although tidal observations which are extracted from coastal tide gages, have higher accuracy due to their higher sampling rate, installing these types of gages can impose some spatial limitation since we cannot use every part of sea to install them. To solve this limitation, we can employ satellite altimetry observations. However, satellite altimetry observations have lower sampling rate. Acco...