Weighted Covairance Calculation [SAS]

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From: sid on 15 Jun 2010 05:06

Hi,
I am trying to find out the covariance of weighted (aggregated) data.
I want help with the code which gives me the covariance matrix. I have
written the following code to calculate the covariance but I am not
able to create any matrix. Please help me with the code. I have also
attached a small sample data set.

CODE USED:
proc corr data =thesis.weekwt3 COV NOCORR vardef=weight
outp=thesis.weekwt4;
by sensor_id s_hour am_pm;
weight volume;
var traveltime;
run;

SAMPLE DATA SET:
sensor_id date s_hour s_min s_sec am_pm lane volume speed traveltime
direction min_class
110 2/4/2008 7 0 30 am 1 17 56 70.71428571 1 1
110 2/4/2008 7 0 30 am 2 15 44 90 1 1
110 2/4/2008 7 0 30 am 3 17 55 72 . 1
110 2/4/2008 7 0 30 am 4 13 43 92.09302326 . 1
110 2/4/2008 7 1 0 am 1 14 60 66 1 1
110 2/4/2008 7 1 0 am 2 21 43 92.09302326 1 1
110 2/4/2008 7 1 0 am 3 16 56 70.71428571 . 1
110 2/4/2008 7 1 0 am 4 12 66 60 . 1
110 2/4/2008 7 1 30 am 1 11 54 73.33333333 1 1
110 2/4/2008 7 1 30 am 2 23 39 101.5384615 1 1
110 2/4/2008 7 1 30 am 3 3 46 86.08695652 . 1
110 2/4/2008 7 1 30 am 4 15 51 77.64705882 . 1
110 2/4/2008 7 2 0 am 1 7 50 79.2 1 1
110 2/4/2008 7 2 0 am 2 22 60 66 1 1
110 2/4/2008 7 2 0 am 3 11 39 101.5384615 . 1
110 2/4/2008 7 2 0 am 4 2 65 60.92307692 . 1
110 2/4/2008 7 2 30 am 1 13 57 69.47368421 1 1
110 2/4/2008 7 2 30 am 2 9 64 61.875 1 1
110 2/4/2008 7 2 30 am 3 10 43 92.09302326 . 1
110 2/4/2008 7 2 30 am 4 12 39 101.5384615 . 1
110 2/4/2008 7 3 0 am 1 13 43 92.09302326 1 1
110 2/4/2008 7 3 0 am 2 11 60 66 1 1
110 2/4/2008 7 3 0 am 3 15 43 92.09302326 . 1
110 2/4/2008 7 3 0 am 4 16 56 70.71428571 . 1
110 2/4/2008 7 3 30 am 1 12 66 60 1 1
110 2/4/2008 7 3 30 am 2 11 55 72 1 1
110 2/4/2008 7 3 30 am 3 15 44 90 . 1
110 2/4/2008 7 3 30 am 4 33 36 110 . 1
110 2/4/2008 7 4 0 am 1 2 56 70.71428571 1 1
110 2/4/2008 7 4 0 am 2 9 57 69.47368421 1 1
110 2/4/2008 7 4 0 am 3 10 51 77.64705882 . 1
110 2/4/2008 7 4 0 am 4 17 57 69.47368421 . 1
110 2/4/2008 7 4 30 am 1 14 65 60.92307692 1 1
110 2/4/2008 7 4 30 am 2 11 46 86.08695652 1 1
110 2/4/2008 7 4 30 am 3 21 49 80.81632653 . 1
110 2/4/2008 7 4 30 am 4 7 66 60 . 1
110 2/4/2008 7 5 0 am 1 13 54 73.33333333 1 1
110 2/4/2008 7 5 0 am 2 15 49 80.81632653 1 1
110 2/4/2008 7 5 0 am 3 17 39 101.5384615 . 1
110 2/4/2008 7 5 0 am 4 12 54 73.33333333 . 1
110 2/4/2008 7 5 30 am 1 14 56 70.71428571 1 1
110 2/4/2008 7 5 30 am 2 16 44 90 1 1
110 2/4/2008 7 5 30 am 3 11 55 72 . 1
110 2/4/2008 7 5 30 am 4 12 43 92.09302326 . 1
110 2/4/2008 7 6 0 am 1 13 60 66 1 2
110 2/4/2008 7 6 0 am 2 14 43 92.09302326 1 2
110 2/4/2008 7 6 0 am 3 21 56 70.71428571 . 2
110 2/4/2008 7 6 0 am 4 14 66 60 . 2
110 2/4/2008 7 6 30 am 1 16 39 101.5384615 1 2
110 2/4/2008 7 6 30 am 2 12 46 86.08695652 1 2
110 2/4/2008 7 6 30 am 3 9 56 70.71428571 . 2
110 2/4/2008 7 6 30 am 4 12 44 90 . 2
110 2/4/2008 7 7 0 am 1 10 35 113.1428571 1 2
110 2/4/2008 7 7 0 am 2 7 49 80.81632653 1 2
110 2/4/2008 7 7 0 am 3 22 66 60 . 2
110 2/4/2008 7 7 0 am 4 13 60 66 . 2
110 2/4/2008 7 7 30 am 1 14 53 74.71698113 1 2
110 2/4/2008 7 7 30 am 2 11 34 116.4705882 1 2
110 2/4/2008 7 7 30 am 3 22 48 82.5 . 2
110 2/4/2008 7 7 30 am 4 13 60 66 . 2
110 2/4/2008 7 8 0 am 1 6 56 70.71428571 1 2
110 2/4/2008 7 8 0 am 2 9 44 90 1 2
110 2/4/2008 7 8 0 am 3 10 55 72 . 2
110 2/4/2008 7 8 0 am 4 23 43 92.09302326 . 2
110 2/4/2008 7 8 30 am 1 15 60 66 1 2
110 2/4/2008 7 8 30 am 2 24 43 92.09302326 1 2
110 2/4/2008 7 8 30 am 3 22 56 70.71428571 . 2
110 2/4/2008 7 8 30 am 4 11 66 60 . 2
110 2/4/2008 7 9 0 am 1 14 45 88 1 2
110 2/4/2008 7 9 0 am 2 12 55 72 1 2
110 2/4/2008 7 9 0 am 3 13 46 86.08695652 . 2
110 2/4/2008 7 9 0 am 4 18 51 77.64705882 . 2
234 2/4/2008 7 0 30 am 1 21 35 72 1 1
234 2/4/2008 7 0 30 am 2 14 49 51.42857143 1 1
234 2/4/2008 7 0 30 am 3 16 66 38.18181818 . 1
234 2/4/2008 7 0 30 am 4 12 60 42 . 1
234 2/4/2008 7 1 0 am 1 9 53 47.54716981 1 1
234 2/4/2008 7 1 0 am 2 12 34 74.11764706 1 1
234 2/4/2008 7 1 0 am 3 10 48 52.5 . 1
234 2/4/2008 7 1 0 am 4 7 60 42 . 1
234 2/4/2008 7 1 30 am 1 22 56 45 1 1
234 2/4/2008 7 1 30 am 2 13 44 57.27272727 1 1
234 2/4/2008 7 1 30 am 3 14 55 45.81818182 . 1
234 2/4/2008 7 1 30 am 4 11 43 58.60465116 . 1
234 2/4/2008 7 2 0 am 1 14 60 42 1 1
234 2/4/2008 7 2 0 am 2 13 43 58.60465116 1 1
234 2/4/2008 7 2 0 am 3 17 56 45 . 1
234 2/4/2008 7 2 0 am 4 7 66 38.18181818 . 1
234 2/4/2008 7 2 30 am 1 9 45 56 1 1
234 2/4/2008 7 2 30 am 2 10 55 45.81818182 1 1
234 2/4/2008 7 2 30 am 3 14 46 54.7826087 . 1
234 2/4/2008 7 2 30 am 4 13 51 49.41176471 . 1
234 2/4/2008 7 3 0 am 1 11 51 49.41176471 1 1
234 2/4/2008 7 3 0 am 2 13 50 50.4 1 1
234 2/4/2008 7 3 0 am 3 6 60 42 . 1
234 2/4/2008 7 3 0 am 4 9 39 64.61538462 . 1
234 2/4/2008 7 3 30 am 1 10 65 38.76923077 1 1
234 2/4/2008 7 3 30 am 2 23 57 44.21052632 1 1
234 2/4/2008 7 3 30 am 3 15 64 39.375 . 1
234 2/4/2008 7 3 30 am 4 24 43 58.60465116 . 1
234 2/4/2008 7 4 0 am 1 22 39 64.61538462 1 1
234 2/4/2008 7 4 0 am 2 11 43 58.60465116 1 1
234 2/4/2008 7 4 0 am 3 14 60 42 . 1
234 2/4/2008 7 4 0 am 4 12 43 58.60465116 . 1
234 2/4/2008 7 4 30 am 1 13 56 45 1 1
234 2/4/2008 7 4 30 am 2 18 66 38.18181818 1 1
234 2/4/2008 7 4 30 am 3 17 55 45.81818182 . 1
234 2/4/2008 7 4 30 am 4 15 43 58.60465116 . 1
234 2/4/2008 7 5 0 am 1 17 60 42 1 1
234 2/4/2008 7 5 0 am 2 13 43 58.60465116 1 1
234 2/4/2008 7 5 0 am 3 14 56 45 . 1
234 2/4/2008 7 5 0 am 4 21 66 38.18181818 . 1
234 2/4/2008 7 5 30 am 1 16 54 46.66666667 1 1
234 2/4/2008 7 5 30 am 2 12 39 64.61538462 1 1
234 2/4/2008 7 5 30 am 3 11 46 54.7826087 . 1
234 2/4/2008 7 5 30 am 4 23 51 49.41176471 . 1
234 2/4/2008 7 6 0 am 1 3 51 49.41176471 1 2
234 2/4/2008 7 6 0 am 2 15 50 50.4 1 2
234 2/4/2008 7 6 0 am 3 7 60 42 . 2
234 2/4/2008 7 6 0 am 4 22 39 64.61538462 . 2
234 2/4/2008 7 6 30 am 1 11 65 38.76923077 1 2
234 2/4/2008 7 6 30 am 2 2 57 44.21052632 1 2
234 2/4/2008 7 6 30 am 3 13 64 39.375 . 2
234 2/4/2008 7 6 30 am 4 9 43 58.60465116 . 2
234 2/4/2008 7 7 0 am 1 10 39 64.61538462 1 2
234 2/4/2008 7 7 0 am 2 15 43 58.60465116 1 2
234 2/4/2008 7 7 0 am 3 16 49 51.42857143 . 2
234 2/4/2008 7 7 0 am 4 12 66 38.18181818 . 2
234 2/4/2008 7 7 30 am 1 11 54 46.66666667 1 2
234 2/4/2008 7 7 30 am 2 15 49 51.42857143 1 2
234 2/4/2008 7 7 30 am 3 33 39 64.61538462 . 2
234 2/4/2008 7 7 30 am 4 2 54 46.66666667 . 2
234 2/4/2008 7 8 0 am 1 9 56 45 1 2
234 2/4/2008 7 8 0 am 2 10 44 57.27272727 1 2
234 2/4/2008 7 8 0 am 3 17 55 45.81818182 . 2
234 2/4/2008 7 8 0 am 4 15 56 45 . 2
234 2/4/2008 7 8 30 am 1 11 46 54.7826087 1 2
234 2/4/2008 7 8 30 am 2 10 49 51.42857143 1 2
234 2/4/2008 7 8 30 am 3 18 53 47.54716981 . 2
234 2/4/2008 7 8 30 am 4 9 39 64.61538462 . 2
234 2/4/2008 7 9 0 am 1 14 68 37.05882353 1 2
234 2/4/2008 7 9 0 am 2 8 61 41.31147541 1 2
234 2/4/2008 7 9 0 am 3 16 57 44.21052632 . 2
234 2/4/2008 7 9 0 am 4 9 47 53.61702128 . 2

From: sid on 15 Jun 2010 13:14

On Jun 15, 4:06 am, sid <siddharth8...(a)gmail.com> wrote:
> Hi,
> I am trying to find out the covariance of weighted (aggregated) data.
> I want help with the code which gives me the covariance matrix. I have
> written the following code to calculate the covariance but I am not
> able to create any matrix. Please help me with the code. I have also
> attached a small sample data set.
>
> CODE USED:
> proc corr data =thesis.weekwt3 COV NOCORR vardef=weight
> outp=thesis.weekwt4;
> by sensor_id s_hour am_pm;
> weight volume;
> var traveltime;
> run;
>
> SAMPLE DATA SET:
> sensor_id date s_hour s_min s_sec am_pm lane volume speed traveltime
> direction min_class
> 110 2/4/2008 7 0 30 am 1 17 56 70.71428571 1 1
> 110 2/4/2008 7 0 30 am 2 15 44 90 1 1
> 110 2/4/2008 7 0 30 am 3 17 55 72 . 1
> 110 2/4/2008 7 0 30 am 4 13 43 92.09302326 . 1
> 110 2/4/2008 7 1 0 am 1 14 60 66 1 1
> 110 2/4/2008 7 1 0 am 2 21 43 92.09302326 1 1
> 110 2/4/2008 7 1 0 am 3 16 56 70.71428571 . 1
> 110 2/4/2008 7 1 0 am 4 12 66 60 . 1
> 110 2/4/2008 7 1 30 am 1 11 54 73.33333333 1 1
> 110 2/4/2008 7 1 30 am 2 23 39 101.5384615 1 1
> 110 2/4/2008 7 1 30 am 3 3 46 86.08695652 . 1
> 110 2/4/2008 7 1 30 am 4 15 51 77.64705882 . 1
> 110 2/4/2008 7 2 0 am 1 7 50 79.2 1 1
> 110 2/4/2008 7 2 0 am 2 22 60 66 1 1
> 110 2/4/2008 7 2 0 am 3 11 39 101.5384615 . 1
> 110 2/4/2008 7 2 0 am 4 2 65 60.92307692 . 1
> 110 2/4/2008 7 2 30 am 1 13 57 69.47368421 1 1
> 110 2/4/2008 7 2 30 am 2 9 64 61.875 1 1
> 110 2/4/2008 7 2 30 am 3 10 43 92.09302326 . 1
> 110 2/4/2008 7 2 30 am 4 12 39 101.5384615 . 1
> 110 2/4/2008 7 3 0 am 1 13 43 92.09302326 1 1
> 110 2/4/2008 7 3 0 am 2 11 60 66 1 1
> 110 2/4/2008 7 3 0 am 3 15 43 92.09302326 . 1
> 110 2/4/2008 7 3 0 am 4 16 56 70.71428571 . 1
> 110 2/4/2008 7 3 30 am 1 12 66 60 1 1
> 110 2/4/2008 7 3 30 am 2 11 55 72 1 1
> 110 2/4/2008 7 3 30 am 3 15 44 90 . 1
> 110 2/4/2008 7 3 30 am 4 33 36 110 . 1
> 110 2/4/2008 7 4 0 am 1 2 56 70.71428571 1 1
> 110 2/4/2008 7 4 0 am 2 9 57 69.47368421 1 1
> 110 2/4/2008 7 4 0 am 3 10 51 77.64705882 . 1
> 110 2/4/2008 7 4 0 am 4 17 57 69.47368421 . 1
> 110 2/4/2008 7 4 30 am 1 14 65 60.92307692 1 1
> 110 2/4/2008 7 4 30 am 2 11 46 86.08695652 1 1
> 110 2/4/2008 7 4 30 am 3 21 49 80.81632653 . 1
> 110 2/4/2008 7 4 30 am 4 7 66 60 . 1
> 110 2/4/2008 7 5 0 am 1 13 54 73.33333333 1 1
> 110 2/4/2008 7 5 0 am 2 15 49 80.81632653 1 1
> 110 2/4/2008 7 5 0 am 3 17 39 101.5384615 . 1
> 110 2/4/2008 7 5 0 am 4 12 54 73.33333333 . 1
> 110 2/4/2008 7 5 30 am 1 14 56 70.71428571 1 1
> 110 2/4/2008 7 5 30 am 2 16 44 90 1 1
> 110 2/4/2008 7 5 30 am 3 11 55 72 . 1
> 110 2/4/2008 7 5 30 am 4 12 43 92.09302326 . 1
> 110 2/4/2008 7 6 0 am 1 13 60 66 1 2
> 110 2/4/2008 7 6 0 am 2 14 43 92.09302326 1 2
> 110 2/4/2008 7 6 0 am 3 21 56 70.71428571 . 2
> 110 2/4/2008 7 6 0 am 4 14 66 60 . 2
> 110 2/4/2008 7 6 30 am 1 16 39 101.5384615 1 2
> 110 2/4/2008 7 6 30 am 2 12 46 86.08695652 1 2
> 110 2/4/2008 7 6 30 am 3 9 56 70.71428571 . 2
> 110 2/4/2008 7 6 30 am 4 12 44 90 . 2
> 110 2/4/2008 7 7 0 am 1 10 35 113.1428571 1 2
> 110 2/4/2008 7 7 0 am 2 7 49 80.81632653 1 2
> 110 2/4/2008 7 7 0 am 3 22 66 60 . 2
> 110 2/4/2008 7 7 0 am 4 13 60 66 . 2
> 110 2/4/2008 7 7 30 am 1 14 53 74.71698113 1 2
> 110 2/4/2008 7 7 30 am 2 11 34 116.4705882 1 2
> 110 2/4/2008 7 7 30 am 3 22 48 82.5 . 2
> 110 2/4/2008 7 7 30 am 4 13 60 66 . 2
> 110 2/4/2008 7 8 0 am 1 6 56 70.71428571 1 2
> 110 2/4/2008 7 8 0 am 2 9 44 90 1 2
> 110 2/4/2008 7 8 0 am 3 10 55 72 . 2
> 110 2/4/2008 7 8 0 am 4 23 43 92.09302326 . 2
> 110 2/4/2008 7 8 30 am 1 15 60 66 1 2
> 110 2/4/2008 7 8 30 am 2 24 43 92.09302326 1 2
> 110 2/4/2008 7 8 30 am 3 22 56 70.71428571 . 2
> 110 2/4/2008 7 8 30 am 4 11 66 60 . 2
> 110 2/4/2008 7 9 0 am 1 14 45 88 1 2
> 110 2/4/2008 7 9 0 am 2 12 55 72 1 2
> 110 2/4/2008 7 9 0 am 3 13 46 86.08695652 . 2
> 110 2/4/2008 7 9 0 am 4 18 51 77.64705882 . 2
> 234 2/4/2008 7 0 30 am 1 21 35 72 1 1
> 234 2/4/2008 7 0 30 am 2 14 49 51.42857143 1 1
> 234 2/4/2008 7 0 30 am 3 16 66 38.18181818 . 1
> 234 2/4/2008 7 0 30 am 4 12 60 42 . 1
> 234 2/4/2008 7 1 0 am 1 9 53 47.54716981 1 1
> 234 2/4/2008 7 1 0 am 2 12 34 74.11764706 1 1
> 234 2/4/2008 7 1 0 am 3 10 48 52.5 . 1
> 234 2/4/2008 7 1 0 am 4 7 60 42 . 1
> 234 2/4/2008 7 1 30 am 1 22 56 45 1 1
> 234 2/4/2008 7 1 30 am 2 13 44 57.27272727 1 1
> 234 2/4/2008 7 1 30 am 3 14 55 45.81818182 . 1
> 234 2/4/2008 7 1 30 am 4 11 43 58.60465116 . 1
> 234 2/4/2008 7 2 0 am 1 14 60 42 1 1
> 234 2/4/2008 7 2 0 am 2 13 43 58.60465116 1 1
> 234 2/4/2008 7 2 0 am 3 17 56 45 . 1
> 234 2/4/2008 7 2 0 am 4 7 66 38.18181818 . 1
> 234 2/4/2008 7 2 30 am 1 9 45 56 1 1
> 234 2/4/2008 7 2 30 am 2 10 55 45.81818182 1 1
> 234 2/4/2008 7 2 30 am 3 14 46 54.7826087 . 1
> 234 2/4/2008 7 2 30 am 4 13 51 49.41176471 . 1
> 234 2/4/2008 7 3 0 am 1 11 51 49.41176471 1 1
> 234 2/4/2008 7 3 0 am 2 13 50 50.4 1 1
> 234 2/4/2008 7 3 0 am 3 6 60 42 . 1
> 234 2/4/2008 7 3 0 am 4 9 39 64.61538462 . 1
> 234 2/4/2008 7 3 30 am 1 10 65 38.76923077 1 1
> 234 2/4/2008 7 3 30 am 2 23 57 44.21052632 1 1
> 234 2/4/2008 7 3 30 am 3 15 64 39.375 . 1
> 234 2/4/2008 7 3 30 am 4 24 43 58.60465116 . 1
> 234 2/4/2008 7 4 0 am 1 22 39 64.61538462 1 1
> 234 2/4/2008 7 4 0 am 2 11 43 58.60465116 1 1
> 234 2/4/2008 7 4 0 am 3 14 60 42 . 1
> 234 2/4/2008 7 4 0 am 4 12 43 58.60465116 . 1
> 234 2/4/2008 7 4 30 am 1 13 56 45 1 1
> 234 2/4/2008 7 4 30 am 2 18 66 38.18181818 1 1
> 234 2/4/2008 7 4 30 am 3 17 55 45.81818182 . 1
> 234 2/4/2008 7 4 30 am 4 15 43 58.60465116 . 1
> 234 2/4/2008 7 5 0 am 1 17 60 42 1 1
> 234 2/4/2008 7 5 0 am 2 13 43 58.60465116 1 1
> 234 2/4/2008 7 5 0 am 3 14 56 45 . 1
> 234 2/4/2008 7 5 0 am 4 21 66 38.18181818 . 1
> 234 2/4/2008 7 5 30 am 1 16 54 46.66666667 1 1
> 234 2/4/2008 7 5 30 am 2 12 39 64.61538462 1 1
> 234 2/4/2008 7 5 30 am 3 11 46 54.7826087 . 1
> 234 2/4/2008 7 5 30 am 4 23 51 49.41176471 . 1
> 234 2/4/2008 7 6 0 am 1 3 51 49.41176471 1 2
> 234 2/4/2008 7 6 0 am 2 15 50 50.4 1 2
> 234 2/4/2008 7 6 0 am 3 7 60 42 . 2
> 234 2/4/2008 7 6 0 am 4 22 39 64.61538462 . 2
> 234 2/4/2008 7 6 30 am 1 11 65 38.76923077 1 2
> 234 2/4/2008 7 6 30 am 2 2 57 44.21052632 1 2
> 234 2/4/2008 7 6 30 am 3 13 64 39.375 . 2
> 234 2/4/2008 7 6 30 am 4 9 43 58.60465116 . 2
> 234 2/4/2008 7 7 0 am 1 10 39 64.61538462 1 2
> 234 2/4/2008 7 7 0 am 2 15 43 58.60465116 1 2
> 234 2/4/2008 7 7 0 am 3 16 49 51.42857143 . 2
> 234 2/4/2008 7 7 0 am 4 12 66 38.18181818 . 2
> 234 2/4/2008 7 7 30 am 1 11 54 46.66666667 1 2
> 234 2/4/2008 7 7 30 am 2 15 49 51.42857143 1 2
> 234 2/4/2008 7 7 30 am 3 33 39 64.61538462 . 2
> 234 2/4/2008 7 7 30 am 4 2 54 46.66666667 . 2
> 234 2/4/2008 7 8 0 am 1 9 56 45 1 2
> 234 2/4/2008 7 8 0 am 2 10 44 57.27272727 1 2
> 234 2/4/2008 7 8 0 am 3 17 55 45.81818182 . 2
> 234 2/4/2008 7 8 0 am 4 15 56 45 . 2
> 234 2/4/2008 7 8 30 am 1 11 46 54.7826087 1 2
> 234 2/4/2008 7 8 30 am 2 10 49 51.42857143 1 2
> 234 2/4/2008 7 8 30 am 3 18 53 47.54716981 . 2
> 234 2/4/2008 7 8 30 am 4 9 39 64.61538462 . 2
> 234 2/4/2008 7 9 0 am 1 14 68 37.05882353 1 2
> 234 2/4/2008 7 9 0 am 2 8 61 41.31147541 1 2
> 234 2/4/2008 7 9 0 am 3 16 57 44.21052632 . 2
> 234 2/4/2008 7 9 0 am 4 9 47 53.61702128 . 2

i actually want the covariance matrix for the traveltimes of the 2
sensor id's. weight is the volume. thanks.

From: sid on 24 Jun 2010 03:44

On Jun 15, 12:14 pm, sid <siddharth8...(a)gmail.com> wrote:
> On Jun 15, 4:06 am, sid <siddharth8...(a)gmail.com> wrote:
>
> > Hi,
> > I am trying to find out the covariance of weighted (aggregated) data.
> > I want help with the code which gives me the covariance matrix. I have
> > written the following code to calculate the covariance but I am not
> > able to create any matrix. Please help me with the code. I have also
> > attached a small sample data set.
>
> > CODE USED:
> > proc corr data =thesis.weekwt3 COV NOCORR vardef=weight
> > outp=thesis.weekwt4;
> > by sensor_id s_hour am_pm;
> > weight volume;
> > var traveltime;
> > run;
>
> > SAMPLE DATA SET:
> > sensor_id date s_hour s_min s_sec am_pm lane volume speed traveltime
> > direction min_class
> > 110 2/4/2008 7 0 30 am 1 17 56 70.71428571 1 1
> > 110 2/4/2008 7 0 30 am 2 15 44 90 1 1
> > 110 2/4/2008 7 0 30 am 3 17 55 72 . 1
> > 110 2/4/2008 7 0 30 am 4 13 43 92.09302326 . 1
> > 110 2/4/2008 7 1 0 am 1 14 60 66 1 1
> > 110 2/4/2008 7 1 0 am 2 21 43 92.09302326 1 1
> > 110 2/4/2008 7 1 0 am 3 16 56 70.71428571 . 1
> > 110 2/4/2008 7 1 0 am 4 12 66 60 . 1
> > 110 2/4/2008 7 1 30 am 1 11 54 73.33333333 1 1
> > 110 2/4/2008 7 1 30 am 2 23 39 101.5384615 1 1
> > 110 2/4/2008 7 1 30 am 3 3 46 86.08695652 . 1
> > 110 2/4/2008 7 1 30 am 4 15 51 77.64705882 . 1
> > 110 2/4/2008 7 2 0 am 1 7 50 79.2 1 1
> > 110 2/4/2008 7 2 0 am 2 22 60 66 1 1
> > 110 2/4/2008 7 2 0 am 3 11 39 101.5384615 . 1
> > 110 2/4/2008 7 2 0 am 4 2 65 60.92307692 . 1
> > 110 2/4/2008 7 2 30 am 1 13 57 69.47368421 1 1
> > 110 2/4/2008 7 2 30 am 2 9 64 61.875 1 1
> > 110 2/4/2008 7 2 30 am 3 10 43 92.09302326 . 1
> > 110 2/4/2008 7 2 30 am 4 12 39 101.5384615 . 1
> > 110 2/4/2008 7 3 0 am 1 13 43 92.09302326 1 1
> > 110 2/4/2008 7 3 0 am 2 11 60 66 1 1
> > 110 2/4/2008 7 3 0 am 3 15 43 92.09302326 . 1
> > 110 2/4/2008 7 3 0 am 4 16 56 70.71428571 . 1
> > 110 2/4/2008 7 3 30 am 1 12 66 60 1 1
> > 110 2/4/2008 7 3 30 am 2 11 55 72 1 1
> > 110 2/4/2008 7 3 30 am 3 15 44 90 . 1
> > 110 2/4/2008 7 3 30 am 4 33 36 110 . 1
> > 110 2/4/2008 7 4 0 am 1 2 56 70.71428571 1 1
> > 110 2/4/2008 7 4 0 am 2 9 57 69.47368421 1 1
> > 110 2/4/2008 7 4 0 am 3 10 51 77.64705882 . 1
> > 110 2/4/2008 7 4 0 am 4 17 57 69.47368421 . 1
> > 110 2/4/2008 7 4 30 am 1 14 65 60.92307692 1 1
> > 110 2/4/2008 7 4 30 am 2 11 46 86.08695652 1 1
> > 110 2/4/2008 7 4 30 am 3 21 49 80.81632653 . 1
> > 110 2/4/2008 7 4 30 am 4 7 66 60 . 1
> > 110 2/4/2008 7 5 0 am 1 13 54 73.33333333 1 1
> > 110 2/4/2008 7 5 0 am 2 15 49 80.81632653 1 1
> > 110 2/4/2008 7 5 0 am 3 17 39 101.5384615 . 1
> > 110 2/4/2008 7 5 0 am 4 12 54 73.33333333 . 1
> > 110 2/4/2008 7 5 30 am 1 14 56 70.71428571 1 1
> > 110 2/4/2008 7 5 30 am 2 16 44 90 1 1
> > 110 2/4/2008 7 5 30 am 3 11 55 72 . 1
> > 110 2/4/2008 7 5 30 am 4 12 43 92.09302326 . 1
> > 110 2/4/2008 7 6 0 am 1 13 60 66 1 2
> > 110 2/4/2008 7 6 0 am 2 14 43 92.09302326 1 2
> > 110 2/4/2008 7 6 0 am 3 21 56 70.71428571 . 2
> > 110 2/4/2008 7 6 0 am 4 14 66 60 . 2
> > 110 2/4/2008 7 6 30 am 1 16 39 101.5384615 1 2
> > 110 2/4/2008 7 6 30 am 2 12 46 86.08695652 1 2
> > 110 2/4/2008 7 6 30 am 3 9 56 70.71428571 . 2
> > 110 2/4/2008 7 6 30 am 4 12 44 90 . 2
> > 110 2/4/2008 7 7 0 am 1 10 35 113.1428571 1 2
> > 110 2/4/2008 7 7 0 am 2 7 49 80.81632653 1 2
> > 110 2/4/2008 7 7 0 am 3 22 66 60 . 2
> > 110 2/4/2008 7 7 0 am 4 13 60 66 . 2
> > 110 2/4/2008 7 7 30 am 1 14 53 74.71698113 1 2
> > 110 2/4/2008 7 7 30 am 2 11 34 116.4705882 1 2
> > 110 2/4/2008 7 7 30 am 3 22 48 82.5 . 2
> > 110 2/4/2008 7 7 30 am 4 13 60 66 . 2
> > 110 2/4/2008 7 8 0 am 1 6 56 70.71428571 1 2
> > 110 2/4/2008 7 8 0 am 2 9 44 90 1 2
> > 110 2/4/2008 7 8 0 am 3 10 55 72 . 2
> > 110 2/4/2008 7 8 0 am 4 23 43 92.09302326 . 2
> > 110 2/4/2008 7 8 30 am 1 15 60 66 1 2
> > 110 2/4/2008 7 8 30 am 2 24 43 92.09302326 1 2
> > 110 2/4/2008 7 8 30 am 3 22 56 70.71428571 . 2
> > 110 2/4/2008 7 8 30 am 4 11 66 60 . 2
> > 110 2/4/2008 7 9 0 am 1 14 45 88 1 2
> > 110 2/4/2008 7 9 0 am 2 12 55 72 1 2
> > 110 2/4/2008 7 9 0 am 3 13 46 86.08695652 . 2
> > 110 2/4/2008 7 9 0 am 4 18 51 77.64705882 . 2
> > 234 2/4/2008 7 0 30 am 1 21 35 72 1 1
> > 234 2/4/2008 7 0 30 am 2 14 49 51.42857143 1 1
> > 234 2/4/2008 7 0 30 am 3 16 66 38.18181818 . 1
> > 234 2/4/2008 7 0 30 am 4 12 60 42 . 1
> > 234 2/4/2008 7 1 0 am 1 9 53 47.54716981 1 1
> > 234 2/4/2008 7 1 0 am 2 12 34 74.11764706 1 1
> > 234 2/4/2008 7 1 0 am 3 10 48 52.5 . 1
> > 234 2/4/2008 7 1 0 am 4 7 60 42 . 1
> > 234 2/4/2008 7 1 30 am 1 22 56 45 1 1
> > 234 2/4/2008 7 1 30 am 2 13 44 57.27272727 1 1
> > 234 2/4/2008 7 1 30 am 3 14 55 45.81818182 . 1
> > 234 2/4/2008 7 1 30 am 4 11 43 58.60465116 . 1
> > 234 2/4/2008 7 2 0 am 1 14 60 42 1 1
> > 234 2/4/2008 7 2 0 am 2 13 43 58.60465116 1 1
> > 234 2/4/2008 7 2 0 am 3 17 56 45 . 1
> > 234 2/4/2008 7 2 0 am 4 7 66 38.18181818 . 1
> > 234 2/4/2008 7 2 30 am 1 9 45 56 1 1
> > 234 2/4/2008 7 2 30 am 2 10 55 45.81818182 1 1
> > 234 2/4/2008 7 2 30 am 3 14 46 54.7826087 . 1
> > 234 2/4/2008 7 2 30 am 4 13 51 49.41176471 . 1
> > 234 2/4/2008 7 3 0 am 1 11 51 49.41176471 1 1
> > 234 2/4/2008 7 3 0 am 2 13 50 50.4 1 1
> > 234 2/4/2008 7 3 0 am 3 6 60 42 . 1
> > 234 2/4/2008 7 3 0 am 4 9 39 64.61538462 . 1
> > 234 2/4/2008 7 3 30 am 1 10 65 38.76923077 1 1
> > 234 2/4/2008 7 3 30 am 2 23 57 44.21052632 1 1
> > 234 2/4/2008 7 3 30 am 3 15 64 39.375 . 1
> > 234 2/4/2008 7 3 30 am 4 24 43 58.60465116 . 1
> > 234 2/4/2008 7 4 0 am 1 22 39 64.61538462 1 1
> > 234 2/4/2008 7 4 0 am 2 11 43 58.60465116 1 1
> > 234 2/4/2008 7 4 0 am 3 14 60 42 . 1
> > 234 2/4/2008 7 4 0 am 4 12 43 58.60465116 . 1
> > 234 2/4/2008 7 4 30 am 1 13 56 45 1 1
> > 234 2/4/2008 7 4 30 am 2 18 66 38.18181818 1 1
> > 234 2/4/2008 7 4 30 am 3 17 55 45.81818182 . 1
> > 234 2/4/2008 7 4 30 am 4 15 43 58.60465116 . 1
> > 234 2/4/2008 7 5 0 am 1 17 60 42 1 1
> > 234 2/4/2008 7 5 0 am 2 13 43 58.60465116 1 1
> > 234 2/4/2008 7 5 0 am 3 14 56 45 . 1
> > 234 2/4/2008 7 5 0 am 4 21 66 38.18181818 . 1
> > 234 2/4/2008 7 5 30 am 1 16 54 46.66666667 1 1
> > 234 2/4/2008 7 5 30 am 2 12 39 64.61538462 1 1
> > 234 2/4/2008 7 5 30 am 3 11 46 54.7826087 . 1
> > 234 2/4/2008 7 5 30 am 4 23 51 49.41176471 . 1
> > 234 2/4/2008 7 6 0 am 1 3 51 49.41176471 1 2
> > 234 2/4/2008 7 6 0 am 2 15 50 50.4 1 2
> > 234 2/4/2008 7 6 0 am 3 7 60 42 . 2
> > 234 2/4/2008 7 6 0 am 4 22 39 64.61538462 . 2
> > 234 2/4/2008 7 6 30 am 1 11 65 38.76923077 1 2
> > 234 2/4/2008 7 6 30 am 2 2 57 44.21052632 1 2
> > 234 2/4/2008 7 6 30 am 3 13 64 39.375 . 2
> > 234 2/4/2008 7 6 30 am 4 9 43 58.60465116 . 2
> > 234 2/4/2008 7 7 0 am 1 10 39 64.61538462 1 2
> > 234 2/4/2008 7 7 0 am 2 15 43 58.60465116 1 2
> > 234 2/4/2008 7 7 0 am 3 16 49 51.42857143 . 2
> > 234 2/4/2008 7 7 0 am 4 12 66 38.18181818 . 2
> > 234 2/4/2008 7 7 30 am 1 11 54 46.66666667 1 2
> > 234 2/4/2008 7 7 30 am 2 15 49 51.42857143 1 2
> > 234 2/4/2008 7 7 30 am 3 33 39 64.61538462 . 2
> > 234 2/4/2008 7 7 30 am 4 2 54 46.66666667 . 2
> > 234 2/4/2008 7 8 0 am 1 9 56 45 1 2
> > 234 2/4/2008 7 8 0 am 2 10 44 57.27272727 1 2
> > 234 2/4/2008 7 8 0 am 3 17 55 45.81818182 . 2
> > 234 2/4/2008 7 8 0 am 4 15 56 45 . 2
> > 234 2/4/2008 7 8 30 am 1 11 46 54.7826087 1 2
> > 234 2/4/2008 7 8 30 am 2 10 49 51.42857143 1 2
> > 234 2/4/2008 7 8 30 am 3 18 53 47.54716981 . 2
> > 234 2/4/2008 7 8 30 am 4 9 39 64.61538462 . 2
> > 234 2/4/2008 7 9 0 am 1 14 68 37.05882353 1 2
> > 234 2/4/2008 7 9 0 am 2 8 61 41.31147541 1 2
> > 234 2/4/2008 7 9 0 am 3 16 57 44.21052632 . 2
> > 234 2/4/2008 7 9 0 am 4 9 47 53.61702128 . 2
>
> i actually want the covariance matrix for the traveltimes of the 2
> sensor id's. weight is the volume. thanks.

pls help me out.thanks.

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