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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
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Soooooo, what's your question?
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I want to higher the frequency of data from quarter to week. As you can see above, the mood data are merely quarterly.
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Are you able to make assumptiosn about the distribution of weekly frequencies? Can they be assumed to be uniformly distributed throughout any given month?
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Can I get every distribution from the quarterly data and then mimic weekly data? Where can I find such codes?