COMP1799 - Demonstrate the Need for Smooth Functions - Modelling the Shape and Scale Parameters - IT Assignment Help

COMP1799: Demonstrate the Need for Smooth Functions  IT Assignment Help

Assignment Task:

The abdomen data provide information on the abdominal data. Fit different response distributions and
choose the ‘best’ model according to the GAIC criterion:
(a) Load the abdom data and print the variable names.

(b) Fit the normal distribution model, using PB() to fit P-spline smoothers for the predictors for μμ and σσ with automatic selection of smoothing parameters: mNO<- gamlss(y~pb(x), sigma.fo=~pb(x), data=abdom, family=NO)

(c) Try fitting alternative distributions:

a. two-parameter distributions: GA, IG, GU, RG, LO,

b. three-parameter distributions: PE, TF, BCCG,

c. four-parameter distributions: BCT, BCPE.

(d) Apply Pb() to all parameters of each distribution. Make sure to use different model names.

(e) Compare the fitted models using GAIC with each of the penalties k=2, k=3 and k=log(length(abdom$y)), e.g. GAIC(mNO,mGA,mIG,mGU,mRG,mLO,mPE,mTF,mBCCG,mBCT,mBCPE,k=2)

(f) Check the residuals for your chosen model, say m, by plot(m) and wp(m).

(g) For a chosen model, say m, look at the total effective degrees of freedom edfAll(m), plot the fitted parameters, fittedPlot(m,x=abdom,$x), and plot the data by plot(y?x,data=abdom), and fitted μμ against xx, lines(fitted(m)?x, data=abdom).

(h) For a chosen model, examine the centile curves using centiles(m,abdom$x).

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