Statistics 6871: Handouts

Introduction to Splus

• Introduction to Splus

Introduction to R

• Introduction to R

Chapter 1 Problems

• Handout1: prob1_22.r     prob1_22.ssc
• Handout2: prob1_23.r     prob1_23.ssc    Mass.dat (same as varve.dat)

Chapter 1 Examples

• detrending and differencing: jj.dat     jj.xls    jj.mtw    jj.r     jj.ssc
• simulation: simdata.r     simdata.ssc
• ACF CCF soi and recruits: soi.dat     recruits.dat     soi.r     soi.ssc
• smoothing: fig1_22.r     fig1_22.ssc      fig1_23.r     fig1_23.ssc

Bill's explanation of compounding ( what does the difference of the log transformed time series mean? )

• compounding.pdf

• Handout3: solve.m solve.sci   These contain MATLAB and SCILAB code to solve polynomial.
• Handout4: sim.ssc     plot1.pdf plot2.pdf plot3.pdf plot4.pdf plot5.pdf plot6.pdf

Exponential Smoothing Examples SAS

• sunspot data SAS: sunspot.sas
• air passenger data SPSS: air.doc     air.xls     air.sav     air.spo
• air passenger data SAS: airsimple.sas    airholt.sas    airwinters.sas

Chapter 2 Examples

• simulate an ARMA(1,1) model: arma_11.ssc
• fit an AR(p) model to the recruits data: recruit.dat     recruits_ar.r     recruits_ar.ssc
• fit an ARIMA(p,d,q)x(P,D,Q)s model to the production series: prod.dat     production_sarma.r      production_sarma.ssc
• simulated long memory example: fracdiffsim.r    fracdiffsim.ssc

Midterm

• The computer midterm:    midterm2.pdf
• The computer midterm has three datasets: racife.dat securities.dat airpass.dat
• There are two handouts related to performing the Classical Decomposition of a Racife, Brazil Air Temperature data. racife.r racife.ssc
• There are two handouts related to developing an appropriate ARIMA model for the airpass data.  airpass.r airpass.ssc
• Forecasting examples SAS:  For the construction dataset which include three variables, number of contracts (contracts), interest rate (intrate), and hstarts (housing starts) determine the most important exponential smoothing methods.  constr.sas
• Decomposition of a time series and Seasonal Adjustment X11 SAS:  For the electricity dataset the electricity production time series is seasonally adjusted using the decomposition method X11.  Run the program electric.sas and comment on the results.  What do each of the plots show?

Chapter 3 Examples

• generate three cycles: threecycles.ssc    threecycles.r
• spectrum and coherence: recruit.dat     soi.dat     recruits.ssc     recruits.r