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Time series and random processes in linear systems
MTH3230
Synopsis
Multivariate distributions. Estimation: maximum of likelihood and method of moments. Confidence intervals. Analysis in the time domain: stationary models, autocorrelation, partial autocorrelation. ARMA and ARIMA models. Analysis in the frequency domain (Spectral analysis): spectrum, periodigram, linear and digital filters, cross-correlations and cross-spectrum, spectral estimators, confidence interval for the spectral density. State-space models. Kalman filter. Empirical Orthogonal Functions and other Eigen Methods. Use of ITSM.
Sourced from the Monash Handbook 2026.
Quick facts
- Credit points
- 6
- Level
- 3
- Audience
- Undergraduate
- Type
- Coursework
- School
- Faculty of Science
- Faculty
- School of Mathematics
- Handbook year
- 2026
Prerequisites (4)
- Multivariable calculusMTH2010
- Differential equations with modellingMTH2032
- Mathematical modellingMTH2040
- Mathematics of uncertaintyMTH2222
What it unlocks
Nothing in the visible graph depends on this unit.
Offerings (1)
- Second semesterClayton · ON-CAMPUS
Listed in 7 areas of study
- Applied mathematicsAdditional elective unit
- Financial and insurance mathematicsLevel 2 and 3 core units
- MathematicsMathematics elective units
- MathematicsMathematics elective units
- Pure mathematicsPure mathematics elective units
- Mathematical statisticsLevel 3 units
- Mathematical statisticsLevel 2 and 3 units