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16:960:565

Applied Time Series Analysis

Rutgers University 3 credits Statistics

Course Description

Model-based forecasting methods; autoregressive and moving average models; ARIMA, ARMAX, ARCH, and state-space models; estimation, forecasting, and model validation; missing data; irregularly spaced time series; parametric and nonparametric bootstrap methods for time series; multiresolution analysis of spatial and time-series signals; and time-varying models and wavelets. Prerequisite: Level V statistics.

Code
16:960:565
Credits
3
Subject
Statistics

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