Cfrgtkky

I just started working with data analysis and I know basics R. My company used to run forecast models with Eviews and now they asked me to put it all on R so I can run the models as well (I do not have Eviews or know how to use it!). Can anyone please help me? I would also appreciate if you have any material on R to recommend.

The code gets a xls file with multiple variables. Then it runs lots of models with different combinations of those variable, and stores everything in a group (I displayed only the first models because there are more than 100!!). Last, it calculates the MAE and RMSE for each of the models.

Any help is welcome! Thank you very much

'##########################################################                 

'#                                      Modelos para PIM                                    

'##########################################################



'Defines working path

cd " "



' Limpa workfile anterior

close pim_linked.wf1

wfcreate(wf=pim_linked,page=origin) m 1991m01 2020m12

delete *



'Lê dados da pim.xls no worksheet origem

read(s=origem,b2) pim.xls 12



' Define tabela para armazenar resultados

table tab_mom

table tab_yoy



'Linha incrementa a cada modelo

!linha = 1



' Escolher x como o numero até o mês da ultima observação da PIM

!x = @dtoo("2018:06")



'Define  ultima data da amostra

%data = @otod(!x)

%dataproj = @otod(!x + 1)







''''Geral

    group modelo_mom{!linha} dlog(y) c dlog(y(-1)) dlog(abcr) dlog(abcr(-1)) dlog(pmi) dlog(pmi(-1)) dlog(aco) dlog(papond) dlog(anf) dlog(ici) dlog(nuci) dlog(energia) _

                                        @seas(1) @seas(2) @seas(3) @seas(4) @seas(5) @seas(6) @seas(7) @seas(8) @seas(9) @seas(10) @seas(11)    

!linha = !linha + 1

group modelo_mom{!linha} dlog(y) c dlog(y(-1)) dlog(abcr) dlog(abcr(-1)) dlog(pmi) dlog(pmi(-1)) dlog(aco) dlog(papond) dlog(anf) dlog(ici) dlog(nuci) _

                                        @seas(1) @seas(2) @seas(3) @seas(4) @seas(5) @seas(6) @seas(7) @seas(8) @seas(9) @seas(10) @seas(11)    

!linha = !linha + 1

group modelo_mom{!linha} dlog(y) c dlog(y(-1)) dlog(abcr) dlog(abcr(-1)) dlog(pmi) dlog(pmi(-1)) dlog(aco) dlog(papond) dlog(anf) dlog(ici) _

                                        @seas(1) @seas(2) @seas(3) @seas(4) @seas(5) @seas(6) @seas(7) @seas(8) @seas(9) @seas(10) @seas(11)    



!fim = !linha



For !i = 1 To !fim

smpl 2002m01 %data  

equation eqt{!i}.ls(n) modelo_mom{!i}



smpl %dataproj %dataproj

eqt{!i}.forecast proj

y(!x + 1) = proj(!x + 1)



smpl 2002m1 %dataproj                                                                               'Amplia amostra para dessazonalizar

y.x12(mode=a,sfile="P:MacroX12omegav03allx12aPIMeviews.txt")               'Dessazonaliza série



tab_mom(!i,1) = proj(!x + 1)                                                                            'Armazena projeção para y(!x + 1) na primeira coluna

tab_mom(!i,2) = y_sa(!x + 1)                                                                            'Armazena proj y_sa(!x + 1)

tab_mom(!i,3) = eqt{!i}.@rbar2                                                                          'Armazena R^2 ajustado na terceira coluna

tab_mom(!i,4) = eqt{!i}.@aic

tab_mom(!i,5) = eqt{!i}.@schwarz

'tab_mom(!i,6) = eqt.@dw



'Forecast one month ahear, for 12 months

For !j = 1 To 12

    series pim_frcst

    %ultima_data = @otod(!x - !j)

    %data_previsao = @otod(!x - !j + 1)

    smpl 2002m01 %ultima_data

    equation eqt_f.ls(n) modelo_mom{!i}



    smpl %data_previsao %data_previsao

    eqt_f.forecast pim_forecast

    pim_frcst(!x - !j + 1) = pim_forecast(!x - !j + 1)

Next



smpl 2002m01 %data

genr pimF_errs = pim_frcst - y

genr pimF_errs_sqrt = pimF_errs^2

tab_mom(!i,6) = @sqrt(@mean(pimF_errs_sqrt))

tab_mom(!i,7) = @mean(abs(pimF_errs))

tab_mom(!i,8) = (y_sa(!x+1)/y_sa(!x) - 1)*100                                                   'Armazena variação percentual com ajuste sazonal na quinta coluna

Next