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From |
Tirthankar Chakravarty <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Making a Matrix from Three Variables |

Date |
Sat, 9 May 2009 22:39:38 +0100 |

<> <> Many apologies. Read Glenn for Allan. T On Sat, May 9, 2009 at 10:38 PM, Tirthankar Chakravarty <[email protected]> wrote: > <> > <> > 1) Amadou's solution can be streamlined considerably by replacing the > first part as in the code included below. > > 2) The line: > tomata x y z, missing > does not work because -missing- is not a valid option for -tomata- (Gould, SSC). > > 3) Allan's solution is efficient, but you might want to watch out for > missing values in your original data. So, a slight modification is > included below. > > /*** Begin ***/ > /* Simulate some data */ > clear > clear mata > set obs 100 > // create a 20x5 matrix > egen cols = seq(), from(1) to(5) > sort cols > egen rows = seq(), from(1) to(20) > gen var3 = runiform() > > /* Mata solution - I - not flexible */ > sort cols rows /* note sort order */ > qui su rows > scalar define sMvrows = r(max) > qui su cols > scalar define sMvcols = r(max) > mata: > vA = st_data(.,"var3") > mB = colshape(vA,st_numscalar("sMvrows"))' > mB > end > > /* Mata solution - II - Allan's solution modified */ > mata: > real matrix sparse(real matrix x) > { > real matrix y > real scalar k > > y = J(colmax(x[,1]),colmax(x[,2]),.) > for (k=1; k<=rows(x); k++) { > y[x[k,1],x[k,2]] = x[k,3] > } > > return(y) > } > mC = st_data(.,("rows", "cols", "var3")) > mD = sparse(mC) > mD > > /* Check the two solutions are equivalent */ > asserteq(mD, mB) > end > > /*** End ***/ > > On Sat, May 9, 2009 at 7:13 PM, Amadou DIALLO <[email protected]> wrote: >> Hi Allan, >> >> This is my 3 cents solution (have not get the time to put it in a >> formal mata programm, just tested on the command line). I hope it can >> lead you to what you need to achieve if you play around a bit with it. >> >> Best regards. >> >> Amadou. >> >> >> clear >> >> // suppose you have 3 variables x, y, z, with number of observations >> of x+y = number of observations of z >> >> set obs 10 >> >> g x=. >> replace x=1 in 1 >> replace x=2 in 2 >> >> g y=. >> replace y =1 in 1 >> replace y =2 in 2 >> replace y =3 in 3 >> replace y =4 in 4 >> replace y =5 in 5 >> >> //g z = round(uniform(),1) >> >> g z=. >> replace z =1 in 1 >> replace z =2 in 2 >> replace z =3 in 3 >> replace z =4 in 4 >> replace z =5 in 5 >> replace z =6 in 6 >> replace z =7 in 7 >> replace z =8 in 8 >> replace z =9 in 9 >> replace z =10 in 10 >> >> // tomata x y z, missing // Don't know why not working >> tomata x in 1/2 >> tomata y in 1/5 >> tomata z >> >> mata: >> >> c = rows(x) >> d = cols(y') >> M=J(c,d,.) >> for(i=1;i<=d;i++) { >> M[1,i] = z[i] >> k=d+i >> M[c,i] = z[k] >> } >> M >> z >> end >> >> >> >> 2009/5/9, Glenn Goldsmith <[email protected]>: >>> Hi Allan, >>> >>> It seems like what you're after is more-or-less the same as converting from >>> sparse matrix storage, so the mata code here should do the trick: >>> >>> http://www.stata.com/statalist/archive/2009-04/msg00142.html >>> >>> You just need to get your variables into a mata matrix to start with and you >>> should be away: >>> >>> mata : st_view(x=.,.,("var2","var1","var3")) >>> >>> NB: Note the inverted order of var1 and var2. This is because the code for >>> -sparse()- assumes that the first variable provides the row index, and the >>> second variable provides the column index. >>> >>> HTH, >>> >>> Glenn. >>> >>> Allan Joseph Medwick <[email protected]> wrote: >>> >>> Hi, All, >>> >>> I have three variables (var1, var2, var3). I would like to create a >>> matrix where the values of var1 are the columns (ascending), the >>> values of var2 are the rows (also ascending), and the values of var3 >>> are the elements in the matrix. I know there must be a user defined >>> procedure out there to do this, but I haven't been able to find it. >>> >>> Thanks, >>> Allan >>> >>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >>> >> >> >> -- >> --- >> >> Amadou B. DIALLO, PHD >> Development Economist >> Director, Center for Research and Training on Adult Education >> Mayotte, FRANCE >> www.aprosasoma.org >> +262639693250 >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> > > > > -- > To every ω-consistent recursive class κ of formulae there correspond > recursive class signs r, such that neither v Gen r nor Neg(v Gen r) > belongs to Flg(κ) (where v is the free variable of r). > -- To every ω-consistent recursive class κ of formulae there correspond recursive class signs r, such that neither v Gen r nor Neg(v Gen r) belongs to Flg(κ) (where v is the free variable of r). * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Making a Matrix from Three Variables***From:*"Glenn Goldsmith" <[email protected]>

**Re: st: Making a Matrix from Three Variables***From:*Amadou DIALLO <[email protected]>

**Re: st: Making a Matrix from Three Variables***From:*Tirthankar Chakravarty <[email protected]>

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