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MATH3821 Statisical Modelling and Computing

创建日期：2024-07-26 18:07:05

所属分类：经济Economics

标签： MATH3821

Statisical Modelling and Computing

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MATH3821 Statisical Modelling and Computing
The total marks available for this assignment is 20. It will be possible to obtain a raw score above 20, however
the final mark will be the minimum of the raw mark and 20. The assignment is due on Friday July 26 at
5pm and should be submitted through the link titled “Submission link - Assignment 2” on the subject’s
Moodle page. Please combine your work into a single pdf document that includes all relevant R code.
Question 1 [3+4+2+2+5+4=20 Marks]
Let y := (y1, . . . , yn)T . In the univariate scatterplot smoothing problem, yi, i = 1, . . . , n, are responses that
depend on a single predictor xi, through the equation
yi = f(xi) + εi,
where f(·) is a general smooth function, x1 < x2 < · · · < xn, and εi, i = 1, . . . , n, are independent mean 0,
variance σ2 error terms. Our goal is to estimate f := (f(x1), . . . , f(xn))T , and we denote this estimate by
fˆ := (fˆ(x1), . . . , fˆ(xn))T . If we apply a linear smoothing method to compute fˆ , then there always exists an
n× n matrix S such that
fˆ = Sy,
which is called the smoothing matrix. The matrix S depends on x := (x1, . . . , xn)T , the smoothing method
applied, and the smoothing parameter (labelled h below).
In this question we will apply the kernel smoothing method to compute fˆ . In this method
fˆ(xi) =
n∑
j=1
wj(xi)yj , where wj(xi) =
K
(
xj−xi
h
)
∑n
k=1K
(
xk−xi
h
) .
Here h is the smoothing parameter that can be adjusted to manage the bias/variance trade-off and K is the
kernel. The above equation implies that
Sij = wj(xi) =
K
(
xj−xi
h
)
∑n
k=1K
(
xk−xi
h
) ,
where Sij is the ij-th entry of the smoothing matrix S. Below we let x = (x1, . . . , xn)T =
(0, 1/6, 2/6, . . . , 59/60, 10)T and let the kernel K be the standard normal density. The following
code computes S with h = 1.
h=1
n=61
x<-seq(from=0, to=10, length.out=n)
S<-matrix(0,nrow=n,ncol=n)
for(i in 1:n){
S[i,]<-dnorm((x-x[i])/h)/sum(dnorm((x-x[i])/h))
}
1
(a) Suppose that f(x) = x so that f = (f(x1), . . . , f(x61)) = (0, 1/6, . . . , 10)T . Compute the bias vector
b := f − E(fˆ), for h = 1, and use it to plot the bias as a function of x. Does the smoothing method
suffer from boundary bias? Explain you answer. (Hint: we can compute the bias using one of the
formulas given in lecture 14)
(b) Now suppose that f(x) = x cos(10− x) and σ2 = 16, with f = (f(x1), . . . , f(x61))T .

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CS 333 CP1406 KIT308 Economics 701 ECON3740 ECE 5759 BFC3340 FINC2012 COMP4500 MATH3871 FIT3080 18-819C Economic ECO202Y5Y PHY100 FINC-780 Econ 100B EC602 IE582 EE450 COMP9517 WRDS 150B ECON 570 LECTURE 2 ECA5101 ECE 4420 ADAD9311 FIT3031 CS 544 MF 703 CS 6140 KIT501 ENGSCI 344 CSC171 IE 332 FINM8007 21S2 COSC 1114 FE545 E471 SIT102 CSC108 MAT301 IAE 101 COP3503 STAT2004 EC 303 CS1026 STAT1203 MATH3171 ISOM5160 IFN657 FIT2014 ACCT2102 DSCI550 STATS 330 ELEC421 COMP3670 QBUS6840 MEES:698B MAST30027 MIET1077 Economics IFT 6758 FIT5122 BUSN5101 CptS 111 HRMT5502 Math2018 PP 312 INFS3200 CZ3005 CSSE1001 SENG 2011 MKTG 553Q BUFN 640 COMP507 ETF5952 DATA 311 ECE4043 BANK3011 finance M3H623544 HW1 INFS 7410 AI6103 STAT3888 INFS3208 ACCT7103 ECOS3013 PSYCH 20B F79MA STAT3006 ENGG952 2X MGSC 7000 ECE4132 MSF 526 MATH 3033 CDS 511 EEEE4120 EEET2465 ECA5103 MATH2070 ELEC3104 BU51019 EEE8147 ENGR20003 COSC 1107 ETF3200 FNCE 435 MSFI 435 ISyE6420 GENG4405 HW ETC5523 IE 7315 MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A PHIL2617 PHYS3116 MIE250 BCPM0008 ECN 620 QBUS6830 ECSE-415 ECON5102 MGMT20005 MAT 653 ECO 480 COMP 5/600 CSSE 5600 ME 571 7CCMMS61 CS 550 COMP2865 MATH3075 STATS 506 QTM 220 ISYS2120 FIT5106 STAT 153 MKTG3112 ECON2102 ELE2018 COMP3031 MSIN0010 SCC461 MATH237 CS246 CSC3065 CSE 101 ICTWEB411 COMP9313 ECOS 2025 FN620 MATH11111 MATH 3018 KE1068 FINA 6112 C++ MISM 6202 MSIN0105 CSC8631 MECO6935 COMP4121 ACCT2011 DPBS1150 EEL 3701C F19PL OPM 661 CSE 310 CS918 BIOL30001 ACCT3563 BANK3600 MET CS622 MATH367 ACCT5907 Continuing COMP5048 COMP61021 CS3334 GSOE9210 CSCI-570 COMP 5322 HW 2 ALY-6020 IEOR 4706 DATA 200 EBUS504 CGE12412 COMP4108 7SSMM800 ECMM171P MATE50002 CS225 RS 6003 BH2274 ELEC3111 MAT6669 ECON-UA 227 PHIL 1012 7SSMM603 TB028A P6 ECS708 CSC 427 CS6476 CSE 250A A1A2 ITS61504 EECS 376 model HW6 UV0010 ECON 6074 MG4F7 CMP-7030Y INFO3008 BFIP013 ECON 5068 MATH6002 CS3483 PSTAT 131 C31FM CSOR W4246 AAEC 5307 DATA ELEC362 COMSM0047 ECN6006 MA20224 BST351 MATH 323 MATH323 AA2021 COMP3811 COMP2013 IB9X60 INVP001 EMATM0051 COMP220 BLAW1002 E20 TCP8001 ECON61001 EART40005 ECONM1022 MATH 365 MATH 367 ELEC6218 COMP 5812M EDUC 5061M ELEC ENG 1101 equation MATH6174 ST334 C4 EC9570 A33648 EBUS603 ECON47815 stata WFMS0001 PEM102 INF6060 ionically ELECTRICAL MATH 375 MMW 12 MKTG860 ECON60401 ALY6010 SOST20131 Introduction COM3524 MME2 GGR305 JNB 538 EECS101 COMM5030 IEOR E4601 2B CSC336 EN2315 LAW 432 CSC263 MATH2001 OLET1143 CSCB63 SIT772 COMM1170 STAT 441 MS930 INFT3050 GLBH0030 Stat 120B MAST10007 MGEC61 Machine GGR 252H1S ECON7030 Financial Marketing MGMT30019 ECON5120 SDSC 8009 CSC165H1S DSCI 551 3081W ACM41000 ECA 5304 MATH 1064 ECSE444 DATA 604 COMP7105 MIE1615 ECON4004 ENV200H1S EC481 MKT 306 EC1B1 MATH08051 ALY6140 CS260C CSE30 MSIN0226 CS4103 CSC3064 AM16 COMP11212 CSE4101 PSTAT 174 Math 380W CNT 5106C STAT 310 FIN2028 CS5014 STAT 425 COMP 4102A ELEC2140 MANF9544 QRM 9 QRM 8 ECON 457 COMPSCI 4091 MATH 523 DNSC-4211 PEAS 6000 MSIN0180 COMP2119 A2A HT 2022 IB93F0 MAS316/414 ACCT2522 MSIN0181 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ECON7310 FIT 1006 MANAGEMENT MATH3821 MTHM504 CS975 COMM1100 ELEC2133 MMAI 5500 MIS611 ELEC3114 CS 173 ELEC 3105 ISO 9001 IDSC10 Rural livelihoods and globalisati IDSC10 K17 202 CS823 MAST90007 SPG8024 MAT246 EG-264 CVEN2303 INFS1603 3PR3 MN-2508 4CCE1MCP SPG8030 CMT224 Inflation consumption Applying MAT137 CSE 111 DPBS1110 FINS5530 ELEC4613 GSBS6200 COMP4336 Math W54 DIFFERENTIAL 7PAVMALM ACC 1110 ME 3210 MATH2801 MGMT20001 ECON 6202 PSTAT 120B COMP9024 ENG5027 comp3219 ELE00107M ECON20003 ECON2103 FINA2209 MAST20018 LUBS5308M01 MATH2023 Computation COMP1600 CHEM 3X23 BBMM506 FNCE20003 BMET2922 BISM7216 financial ECMT5001 ACST3059 MAST30012 COMP3511 ECOS 2201 MKTG7512 ECON2540 MTH1010 MAT1841 COMP4600 ECON7740 PAPER C331 CAP 6617 ECON2420 ACCT7107 HLTH 7001 ECOS3002 CVEN30010 MAST30021 MATH1014 BIOL1007 ECOS 3010 SWEN90016 BISM7202 ACCT90012 INFO3315 DSCI 553 INFO90002 COMP3419 CITS 3001 EE5731 FINA3326 NFS 284 COMM2501 FIT2104 PHYS3035 RSM260 MAN3080 CHEM30028 MATH2088 ELEC0144 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