Prediction with incomplete past and interpolation of missing values Academic Article

abstract

• A generalized innovation algorithm is used to solve the problems of prediction of future values based on incomplete past and interpolation of missing values of a stationary time series. The emphasis is on the computational aspects and the proposed method is particularly useful when there are several missing values with arbitrary patterns.

authors

• Pourahmadi, Mohsen

published proceedings

• Statistics & Probability Letters

author list (cited authors)

• Cheng, R., & Pourahmadi, M.

citation count

• 12

complete list of authors

• Cheng, R||Pourahmadi, M

publication date

• January 1997

publisher

• Elsevier  Publisher

published in

• Statistics and Probability Letters  Journal

keywords

• Autoregressive Parameters
• Innovation Algorithm
• Stationary Time Series
• Variance Of Errors

Digital Object Identifier (DOI)

• 10.1016/s0167-7152(96)00146-0

start page

• 341

end page

• 346

volume

• 33

issue

• 4

URL

• http://dx.doi.org/10.1016/s0167-7152(96)00146-0