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STAT 457/554 A01 Assignment
创建日期：2024-04-07 17:33:39
所属分类：统计学statistics
标签： STAT 457
autocorrelation function

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STAT 457/554 A01 

Assignment 5: Due 8:30am, April 6
STAT 457: Questions 1 - 4
STAT 554: Questions 1, 3, 4, 5
Submit your R code and plots for Questions 1, 3 and 4.
Upload your solution including R code and plots as one pdf file on the
Brightspace.
1. (5 marks) Let St represent the monthly sales data in “sales” (n = 150). Fit
an ARIMA model to St. Discuss your model fitting in a step-by-step fashion,
presenting your
(a) initial examination of the data,
(b) transformations, if necessary,
(c) identification of ARIMA model,
(d) parameter estimation,
(e) residual diagnostics and model choice.
2. (5 marks) Consider an invertible MA(1) model, xt = wt + θwt−1, where wt is a
white noise series with mean 0 and variance σ2w.
(a) Show that |ρx(1)| ≤ 0.5.
(b) Consider the sample autocorrelation function ρˆx(1) based on n observations
from the model. Is it possible that |ρˆx(1)| > 0.5? Why?
3. (5 marks) Use R to construct the following plots and comment the features in the
ACF and PACF.
(a) Plot the ACF and PACF of the seasonal ARIMA(1, 0, 0)7 with Φ = 0.75.
(b) Plot the ACF and PACF of the seasonal ARIMA(0, 0, 1)7 with Θ = 0.75.
(c) Plot the ACF and PACF of the seasonal ARIMA(1, 0, 1)7 with Φ = 0.75 and
Θ = 0.75.
4. (5 marks) Fit a seasonal ARIMA model to the unemployment data in
“UnempRate”.
(a) Present your model choice and the residual diagnostics.
(b) Use the estimated model to forecast the next 12 months. Present the plot
with the forecasts and the 95% prediction intervals for each of the 12 forecasts.
5. (5 marks) A first-order autoregressive model is generated from the white noise
series wt using the generating equations xt = −0.5xt−1 +wt, where wt is a white
noise series with mean 0 and variance σ2w.
(a) Find the power spectrum function fx(ω) of xt.
(b) Plot fx(ω) vs ω and comment on the power and frequencies in xt.
(c) Let yt = 3xt + 20. Find the power spectrum function fy(ω) of yt.
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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