✦ LIBER ✦

A Regression Model for Estimation of the Seasonal Component in Unemployment and Other Volatile Time Series

✍ Scribed by John A. Brittain

Book ID: 121476347
Publisher: MIT Press
Year: 1962
Tongue: English
Weight: 495 KB
Volume: 44
Category: Article
ISSN: 0034-6535
DOI: 10.2307/1926620

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Selection and estimation of component mo

Selection and estimation of component models for seasonal time series

✍ John Haywood; Granville Tunnicliffe Wilson 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 285 KB 👁 2 views

The Poisson limit theorem for high extre

The Poisson limit theorem for high extrema of a time series with seasonal component and monotone trend

✍ I. V. Rodionov 📂 Article 📅 2012 🏛 Allerton Press Inc 🌐 English ⚖ 937 KB

Time Series and Related Topics: In Memor

Time Series and Related Topics: In Memory of Ching-Zong Wei || Estimation Errors of the Sharpe Ratio for Long-Memory Stochastic Volatility Models

✍ Hwai-Chung Ho 📂 Article 📅 2006 🏛 Institute of Mathematical Statistics ⚖ 715 KB

Pooling Cross Section and Time Series Da

Pooling Cross Section and Time Series Data in the Estimation of a Dynamic Model: The Demand for Natural Gas

✍ Pietro Balestra and Marc Nerlove 📂 Article 📅 1966 🏛 John Wiley and Sons 🌐 English ⚖ 731 KB

A blind method for the estimation of the

A blind method for the estimation of the Hurst exponent in time series: Theory and application

✍ Esposti, Federico; Ferrario, Manuela; Signorini, Maria Gabriella 📂 Article 📅 2008 🏛 American Institute of Physics 🌐 English ⚖ 844 KB

Handbook of Financial Time Series Volume

Handbook of Financial Time Series Volume 49 || Estimating Volatility in the Presence of Market Microstructure Noise: A Review of the Theory and Practical Considerations

✍ Mikosch, Thomas; Kreiß, Jens-Peter; Davis, Richard A.; Andersen, Torben Gustav 📂 Article 📅 2009 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 532 KB

The Handbook Of Financial Time Series Gives An Up-to-date Overview Of The Field And Covers All Relevant Topics Both From A Statistical And An Econometrical Point Of View. There Are Many Fine Contributions, And A Preamble By Nobel Prize Winner Robert F. Engle.