The following is the code I imputed and the log. And the attached is the original data I used. I want to use quarter data to impute weekly data but there is something wrong. I refer to "Multiple Imputation for Missing Data: Concepts and News Development". The attached is the data which has more information because it starts in 2008 quarterly, and I don't know whether it will be useful for monotone or not.
input date search_volume open_price volume mood_prive mood_economic mood_government mood_investment mood_global mood_possibility
;
informat date yymmdd.;
format date yymmdd10.;
datalines;
2013-12-29 31265.96873 8585.37 8868976 . . . . . .
2014-01-05 27950.70473 8553 25542285 . . . . . .
2014-01-12 25902.91541 8587.49 23798004 . . . . . .
2014-01-19 23850.62263 8595.59 21013310 . . . . . .
2014-01-26 16471.45342 8519.48 4003706 102.6 86.4 108.3 94.6 117.5 113.7
2014-02-02 18413.8849 8290.17 13577988 . . . . . .
2014-02-09 22096.8015 8416.42 20932955 . . . . . .
2014-02-16 21174.52948 8537.83 20897446 . . . . . .
2014-02-23 19110.34379 8603.61 18451389 . . . . . .
2014-03-02 20039.02689 8627.15 23866751 . . . . . .
2014-03-09 20082.52542 8706.43 21628830 . . . . . .
2014-03-16 18755.35847 8697.26 22388151 . . . . . .
2014-03-23 18181.1214 8540.27 22001681 . . . . . .
2014-03-30 16583.05049 8802.93 18635131 . . . . . .
2014-04-06 17277.2075 8844.91 23653011 . . . . . .
2014-04-13 16706.70072 8897.23 21848387 . . . . . .
2014-04-20 16448.80356 8961.52 25353783 . . . . . .
2014-04-27 15159.39418 8680.14 19053126 . . . . . .
2014-05-04 16407.68482 8895.87 24751657 . . . . . .
2014-05-11 15863.96562 8893.72 21302355 . . . . . .
2014-05-18 14733.00752 8901.54 21286694 . . . . . .
2014-05-25 14988.46355 9040.49 25196797 100.6 84.7 94.2 93.5 117.6 117.4
2014-06-01 13836.44918 9106.61 21298265 . . . . . .
2014-06-08 14721.77203 9153.93 25439138 . . . . . .
2014-06-15 14364.49877 9196.23 25290129 . . . . . .
2014-06-22 14247.61966 9293.06 24519615 . . . . . .
2014-06-29 13867.25553 9332.44 31407426 . . . . . .
2014-07-06 13952.17408 9497.27 31082280 . . . . . .
2014-07-13 13606.93546 9497.81 30163910 . . . . . .
2014-07-20 12365.85288 9453.78 22175631 . . . . . .
2014-07-27 13382.69317 9415.9 31581958 . . . . . .
2014-08-03 13215.86645 9280.29 28543120 . . . . . .
2014-08-10 12929.63734 9109.83 26019178 . . . . . .
2014-08-17 12262.72744 9222.73 26300484 106 95.6 101.7 99.6 110.8 118.2
2014-08-24 11969.15285 9393.24 28277607 . . . . . .
2014-08-31 12274.05186 9474.41 24938544 . . . . . .
2014-09-07 11168.15524 9452.14 18875091 . . . . . .
2014-09-14 10709.79633 9206.41 22890528 . . . . . .
2014-09-21 10817.08069 9220.54 25272005 . . . . . .
2014-09-28 10663.75135 9018.46 25827744 . . . . . .
2014-10-05 9763.12662 9118.28 18627350 . . . . . .
2014-10-12 10960.82462 8767.42 29734551 . . . . . .
2014-10-19 9997.050868 8617.08 23795287 91 79.5 94.5 87.1 99.7 105.1
2014-10-26 9944.235397 8671.51 26800560 . . . . . .
2014-11-02 9784.14586 9009.38 26105437 . . . . . .
2014-11-09 9546.99488 8937.59 26419817 . . . . . .
2014-11-16 9244.900155 9003.37 26437142 . . . . . .
2014-11-23 8808.63662 9144.42 24429230 . . . . . .
2014-11-30 9175.051622 9038.41 30591366 . . . . . .
2014-12-07 9101.637737 9231.24 26818238 . . . . . .
2014-12-14 9172.5426 8987.95 27376696 . . . . . .
2014-12-21 9123.711552 9032.42 28035931 . . . . . .
2014-12-28 7537.97184 9216.43 12659602 . . . . . .
2015-01-04 8631.193364 9292.31 28375399 . . . . . .
2015-01-11 8838.39816 9198.02 27159441 . . . . . .
2015-01-18 9033.024336 9183.76 28166155 . . . . . .
2015-01-25 8806.864325 9474.56 24158921 107.4 104.3 100.1 103 106.3 112.9
2015-02-01 8292.73749 9368.83 22232706 . . . . . .
2015-02-08 8117.578392 9465.12 19033502 . . . . . .
2015-02-22 6591.595891 9582.39 13351786 . . . . . .
2015-03-01 7429.726695 9665.11 22863592 . . . . . .
2015-03-08 8641.626314 9617.04 24552198 . . . . . .
2015-03-15 8644.147128 9583.45 26949243 . . . . . .
2015-03-22 8632.189365 9759.88 26912945 . . . . . .
2015-03-29 8322.389316 9533.38 19524422 . . . . . .
2015-04-05 7574.663565 9619.97 19816370 . . . . . .
2015-04-12 7734.082764 9622.64 26447471 . . . . . .
2015-04-19 8239.993245 9541.83 31624373 . . . . . .
2015-04-26 7965.947754 9941.18 24944950 103.7 97.8 102.2 100.5 115.8 118.6
2015-05-03 7611.97648 9853.51 27094159 . . . . . .
2015-05-10 7948.371142 9763.94 27128808 . . . . . .
2015-05-17 8049.740643 9603.75 28939396 . . . . . .
2015-05-24 7569.963872 9654.28 28573397 . . . . . .
2015-05-31 7514.023004 9688.13 30180031 . . . . . .
2015-06-07 7687.393563 9324.22 27126930 . . . . . .
2015-06-14 7915.602594 9304.66 18257928 . . . . . .
2015-06-21 6886.880676 9247.76 24704046 . . . . . .
2015-06-28 7376.858034 9358.96 23717485 . . . . . .
2015-07-05 7046.740272 9309.86 23967947 . . . . . .
2015-07-12 6616.456938 8946.72 25460751 . . . . . .
2015-07-19 6883.896656 9085 24447954 . . . . . .
2015-07-26 6811.449276 8733.24 27039490 . . . . . .
2015-08-02 6726.622821 8636.53 24571823 . . . . . .
2015-08-09 6190.303924 8410.63 25408867 81.4 69.1 83.7 69.6 92.4 93.1
2015-08-16 6614.64462 8307.9 24447475 . . . . . .
2015-08-23 6496.243056 7719.63 30520394 . . . . . .
2015-08-30 6772.360023 8026.62 24077331 . . . . . .
2015-09-06 6770.10926 7990.76 22013661 . . . . . .
2015-09-13 6673.061307 8332.57 20866061 . . . . . .
2015-09-20 6459.860415 8404.5 19706723 . . . . . .
2015-09-27 6303.013815 8097.15 13054665 . . . . . .
2015-10-04 5344.697037 8342.99 18792859 . . . . . .
2015-10-11 5971.639212 8478.34 23650100 . . . . . .
2015-10-18 6417.000734 8628.79 22119488 84.7 64.1 86.6 73.7 91.2 97.6
2015-10-25 6091.730304 8706.81 21924824 . . . . . .
2015-11-01 5904.13722 8571.53 26349460 . . . . . .
2015-11-08 6116.07632 8702.67 22765949 . . . . . .
2015-11-15 5822.92998 8278.12 21620246 . . . . . .
2015-11-22 5767.492714 8480.59 19569438 . . . . . .
2015-11-29 5731.552584 8339.83 23294483 . . . . . .
2015-12-06 5951.292566 8432.47 22101131 . . . . . .
2015-12-13 5652.626049 8058.67 21747690 . . . . . .
2015-12-20 5785.745716 8228.05 20148726 . . . . . .
2015-12-27 5513.3874 8374.18 11155757 . . . . . .
2016-01-03 5094.713425 8315.79 23320302 . . . . . .
2016-01-10 5527.809588 7855.8 21796331 . . . . . .
2016-01-17 5461.9691 7678.67 21952700 . . . . . .
2016-01-24 5318.710272 7813.73 25737476 . . . . . .
2016-01-31 5400.46584 8164.24 11065498 . . . . . .
2016-02-14 4178.142814 7976.65 21610384 . . . . . .
2016-02-21 5427.485784 8315.79 21590153 85.5 79.6 91.7 85.3 82.9 90
2016-02-28 5371.5115 8381.38 20276948 . . . . . .
2016-03-06 5165.937 8656.74 25154913 . . . . . .
2016-03-13 5740.33275 8746.48 26346648 . . . . . .
2016-03-20 5487.371846 8826.16 20686409 . . . . . .
2016-03-27 5348.992638 8713.72 20414566 . . . . . .
2016-04-03 5426.780965 8605.16 12636153 . . . . . .
2016-04-10 4641.285 8518.96 20740481 . . . . . .
2016-04-17 5279.359605 8681.8 20052962 . . . . . .
2016-04-24 5220.884313 8541.14 17270378 . . . . . .
2016-05-01 5028.013578 8362.35 15836163 . . . . . .
2016-05-08 4828.00368 8156.65 19280986 75.4 71.3 72.7 75.6 90 95.8
2016-05-15 4990.55814 8035.21 16278554 . . . . . .
2016-05-22 4925.14642 8150.38 19228712 . . . . . .
2016-05-29 4966.103024 8476.62 22543549 . . . . . .
2016-06-05 5009.6448 8605.15 10720144 . . . . . .
2016-06-12 4435.354066 8634.24 17486184 . . . . . .
2016-06-19 4728.062988 8612.26 18839181 . . . . . .
2016-06-26 4876.042706 8406.29 20706989 . . . . . .
2016-07-03 4765.53658 8728.32 14677240 . . . . . .
2016-07-10 4288.459904 8728.23 23517389 . . . . . .
2016-07-17 4874.674527 8952.61 23231017 . . . . . .
2016-07-24 4955.11527 9030.36 21522357 . . . . . .
2016-07-31 4766.036 9008.74 19646459 . . . . . .
2016-08-07 4671.079296 9123.07 21151658 . . . . . .
2016-08-14 4751.418455 9152.36 20933658 . . . . . .
2016-08-21 4553.755556 9004.68 19106001 . . . . . .
2016-08-28 4579.152453 9117.53 20176085 . . . . . .
2016-09-04 4650.93738 9032.38 23003485 . . . . . .
2016-09-11 4853.76 9031.51 10761177 . . . . . .
2016-09-18 3653.548384 9003.41 18435835 . . . . . .
2016-09-25 4451.08752 9229.34 9774466 . . . . . .
2016-10-02 3707.56604 9219.52 15190060 . . . . . .
2016-10-09 4481.242982 9311.79 14099344 . . . . . .
2016-10-16 4135.71384 9150.67 16867995 . . . . . .
2016-10-23 4343.89755 9333.94 16375082 . . . . . .
2016-10-30 4125.372995 9283.2 14558306 76.9 70.8 64.9 74.3 97.7 101.1
2016-11-06 4042.326155 9102.97 21524824 . . . . . .
2016-11-13 4142.02584 8955.27 19979138 . . . . . .
2016-11-20 4099.25934 9009.78 20371341 . . . . . .
2016-11-27 4156.382672 9167.33 21357464 . . . . . .
2016-12-04 4230.616248 9194.46 19210242 . . . . . .
2016-12-11 4051.17895 9402.05 18793745 . . . . . .
2016-12-18 4166.231112 9316.06 15937816 . . . . . .
2016-12-25 3994.563776 9088.99 12375581 . . . . . .
;
proc mi data = final seed=899603 out=miout_final;
var mood_economic mood_government mood_investment mood_global mood_possibility;
monotone
reg(mood_economic mood_government mood_investment mood_global mood_possibility);
run;
proc print data=miout_final;
run;
<log>
685 data final;
686 input date search_volume open_price volume mood_prive mood_economic mood_government mood_investment
686! mood_global mood_possibility
687 ;
688 informat date yymmdd.;
689 format date yymmdd10.;
690 datalines;
NOTE: The data set WORK.FINAL has 155 observations and 10 variables.
NOTE: DATA statement used (Total process time):
real time 0.02 seconds
cpu time 0.00 seconds
846 ;
847 proc mi data = final seed=899603 out=miout_final;
848 var mood_economic mood_government mood_investment mood_global mood_possibility;
849 monotone
850 reg(mood_economic mood_government mood_investment mood_global mood_possibility);
851 run;
WARNING: The imputed variable mood_economic in the MONOTONE statement is the leading variable in the VAR list. Missing
values for this variable will not be imputed.
WARNING: The default number of imputations has been changed from 5 to 25.
ERROR: Each observation has analysis variables either all missing or all observed in the data set.
NOTE: The SAS System stopped processing this step because of errors.
WARNING: The data set WORK.MIOUT_FINAL may be incomplete. When this step was stopped there were 0 observations and 11
variables.
WARNING: Data set WORK.MIOUT_FINAL was not replaced because this step was stopped.
NOTE: PROCEDURE MI used (Total process time):
real time 0.08 seconds
cpu time 0.04 seconds
852 proc print data=miout_final;
853 run;
NOTE: No observations in data set WORK.MIOUT_FINAL.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
Soooooo, what's your question?
I want to higher the frequency of data from quarter to week. As you can see above, the mood data are merely quarterly.
Are you able to make assumptiosn about the distribution of weekly frequencies? Can they be assumed to be uniformly distributed throughout any given month?
Can I get every distribution from the quarterly data and then mimic weekly data? Where can I find such codes?
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