In this question you will consider properties of sample estimatorsin time series context and perform inference and testing. Youmay use R to assist you in calculations, but you should state theformula of any estimator you are calculating as well as the valueyou obtain for the estimator, and if R is used, the R commandutilised. You can either obtain the solution by calculator or R.(a) You are given T = 15 samples from a time series:{y₁,..., y15}= {-0.92, 1.08, 0.20, −0.63, 1.36, 1.33, -1.06,0.11, -1.00, -0.68, 1.81, 1.71, 0.93,-0.75, -2.16}-=Calculate the Sample mean, the Sample ACVF (for lags k0,1,2,3,4) and the Sample ACF (for lags k 0,1,2,3,4) andplot the correlogram. Comment on whether this time seriesdata is pure white noise or not based on the Correlogram youconstruct. Remark on the effect of such a small sample sizeon this conclusion.

In this question you will consider properties of sample estimators in time series context and perform inference and testing. You may use R to assist you in calculations, but you should state the formula of any estimator you are calculating as well as the value you obtain for the estimator, and if R is used, the R command utilised. You can either obtain the solution by calculator or by R. 15 samples from a time series: (a) You are given T {y₁, ..., y15} = {-0.92, 1.08, 0.20, -0.63, 1.36, 1.33, -1.06, = 0.11, -1.00, -0.68, 1.81, 1.71, 0.93,-0.75, -2.16} = =- Calculate the Sample mean, the Sample ACVF (for lags k 0,1,2,3,4) and the Sample ACF (for lags k : 0,1,2,3,4) and plot the correlogram. Comment on whether this time series data is pure white noise or not based on the Correlogram you construct. Remark on the effect of such a small sample size on this conclusion.

In this question you will consider properties of sample estimators in time series context and perform inference and testing. You may use R to assist you in calculations, but you should state the formula of any estimator you are calculating as well as the value you obtain for the estimator, and if R is used, the R command utilised. You can either obtain the solution by calculator or by R. 15 samples from a time series: (a) You are given T {y₁, ..., y15} = {-0.92, 1.08, 0.20, -0.63, 1.36, 1.33, -1.06, = 0.11, -1.00, -0.68, 1.81, 1.71, 0.93,-0.75, -2.16} = =- Calculate the Sample mean, the Sample ACVF (for lags k 0,1,2,3,4) and the Sample ACF (for lags k : 0,1,2,3,4) and plot the correlogram. Comment on whether this time series data is pure white noise or not based on the Correlogram you construct. Remark on the effect of such a small sample size on this conclusion.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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