Predict - Maybe I m not understanding it

Question

I posted earlier today about an error I was getting with using the predict function   I was able to get that corrected  and thought I was on the right path  I have a number of observations  actuals  and I have a few data points that I want to extrapolate or predict   I used lm to create a model  then I tried to use predict with the actual value that will serve as the predictor input  This code is all repeated from my previous post  but here it is  df  lt - read table text          Quarter Coupon      Total 1    quot Dec 06 quot   25027 072  132450574 2    quot Dec 07 quot   76386 820  194154767 3    quot Dec 08 quot   79622 147  221571135 4    quot Dec 09 quot   74114 416  205880072 5    quot Dec 10 quot   70993 058  188666980 6    quot Jun 06 quot   12048 162  139137919 7    quot Jun 07 quot   46889 369  165276325 8    quot Jun 08 quot   84732 537  207074374 9    quot Jun 09 quot   83240 084  221945162 10   quot Jun 10 quot   81970 143  236954249 11   quot Mar 06 quot    3451 248  116811392 12   quot Mar 07 quot   34201 197  155190418 13   quot Mar 08 quot   73232 900  212492488 14   quot Mar 09 quot   70644 948  203663201 15   quot Mar 10 quot   72314 945  203427892 16   quot Mar 11 quot   88708 663  214061240 17   quot Sep 06 quot   15027 252  121285335 18   quot Sep 07 quot   60228 793  195428991 19   quot Sep 08 quot   85507 062  257651399 20   quot Sep 09 quot   77763 365  215048147 21   quot Sep 10 quot   62259 691  168862119   header TRUE   str df   data frame     21 obs  of  3 variables     Quarter     Factor w  24 levels  quot Dec 06 quot   quot Dec 07 quot      1 2 3 4 5 7 8 9 10 11        Coupon  num  25027 76387 79622 74114 70993        Total  num  132450574 194154767 221571135 205880072 188666980      Code  model  lt - lm df Total   df Coupon  data df    gt  model  Call  lm formula   df Total   df Coupon   Coefficients   Intercept     df Coupon     107286259         1349   Predict code  based on previous help    These are the predictor values I want to use to get the predicted value  Quarter   c  quot Jun 11 quot    quot Sep 11 quot    quot Dec 11 quot   Total   c 79037022  83100656  104299800  Coupon   data frame Quarter  Total   Coupon estimate  lt - predict model  newdate   Coupon Total   Now  when I run that  I get this error message  Error in    lt - data frame    tmp     quot estimate quot   value   c 60980 3823396919        replacement has 21 rows  data has 3  My original data frame that I used to build the model had 21 observations in it   I am now trying to predict 3 values based on the model  I either don t truly understand this function  or have an error in my code  Help would be appreciated  Thanks

User · Answer

instead of newdata you are using newdate in your predict code  verify once  and just use Coupon estimate  lt - predict model  Coupon   It will work

User · Answer

Thanks Hong  that was exactly the problem I was running into  The error you get suggests that the number of rows is wrong  but the problem is actually that the model has been trained using a command that ends up with the wrong names for parameters   This is really a critical detail that is entirely non-obvious for lm and so on  Some of the tutorial make reference to doing lines like lm olive Area olive Palmitic  - ending up with variable names of olive Area NOT Area  so creating an entry using anewdata lt -data frame Palmitic 2  can t then be used  If you use lm Area Palmitic data olive  then the variable names are right and prediction works   The real problem is that the error message does not indicate the problem at all      Warning message   anewdata  had 1 rows but variable s  found to have X   rows

User · Answer

First  you want to use  model  lt - lm Total   Coupon  data df    not model  lt -lm df Total   df Coupon  data df    Second  by saying lm Total   Coupon   you are fitting a model that uses Total as the response variable  with Coupon as the predictor  That is  your model is of the form Total   a   b Coupon  with a and b the coefficients to be estimated  Note that the response goes on the left side of the    and the predictor s  on the right   Because of this  when you ask R to give you predicted values for the model  you have to provide a set of new predictor values  ie new values of Coupon  not Total   Third  judging by your specification of newdata  it looks like you re actually after a model to fit Coupon as a function of Total  not the other way around  To do this   model  lt - lm Coupon   Total  data df  new df  lt - data frame Total c 79037022  83100656  104299800   predict model  new df

User · Answer

To avoid error  an important point about the new dataset is the name of independent variable  It must be the same as reported in the model  Another way is to nest the two function without creating a new dataset  model  lt - lm Coupon   Total  data df  predict model  data frame Total c 79037022  83100656  104299800      Pay attention on the model  The next two commands are similar  but for predict function  the first work the second don t work   model  lt - lm Coupon   Total  data df   Ok model  lt - lm df Coupon   df Total   Ko

[r] Predict() - Maybe I'm not understanding it

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