Hi Abraham,
Isn't this what you wanted:
data.frame(all.x, y.hat.new)
p.s: it might be safer to use:
myData
mod1 = lm(sold ~ age + gender, data = myData)
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----------------------------------------------------------------------------------------------
On Wed, Dec 21, 2011 at 12:04 PM, Abraham Mathew <abmathe...@gmail.com>wrote:
>
> I looked into what you suggested and got the following results.
>
> > y.hat.new 1 2 3 4 5 6 7
> > 8 9 10
> 1144.675 1190.714 1236.753 1157.829 1210.445 1203.868 1128.232 1282.792
> 1246.619 1154.540
> 11 12 13 14 15 16 17 18
> 19 20
> 1197.291 1180.848 1253.196 1223.599 1243.330 1207.156 1220.311 1226.888
> 1164.406 1266.350
> 21 22 23 24 25 26 27 28
> 29 30
> 1161.117 1151.252 1272.927 1147.963 1230.176 1138.097 1286.081 1249.907
> 1177.560 1167.694
> 31 32 33 34 35 36 37 38
> 39 40
> 1289.369 1269.638 1170.983 1131.520 1240.042 1194.002 1276.215 1305.812
> 1213.733 1312.389
> 41 42 43 44 45 46 47 48
> 49 50
> 1309.101 1322.255 1121.655 1200.579 1263.061 1184.137 1174.271 1187.425
> 1259.773 1295.947
> 51 52 53 54 55 56 57 58
> 59 60
> 1233.465 1141.386 1292.658 1217.022 1332.120 1134.809 1124.943 1299.235
> 1318.966 1256.484
> 61 62 63 64 65 66 67 68
> 69 70
> 1345.274 1325.543 1315.678 1302.524 1279.504 1358.428 1091.997 1138.036
> 1184.076 1105.151
> 71 72 73 74 75 76 77 78
> 79 80
> 1157.767 1151.190 1075.554 1230.115 1193.941 1101.863 1144.613 1128.171
> 1200.518 1170.922
> 81 82 83 84 85 86 87 88
> 89 90
> 1190.653 1154.479 1167.633 1174.210 1111.728 1213.672 1108.440 1098.574
> 1220.249 1095.286
> 91 92 93 94 95 96 97 98
> 99 100
> 1177.499 1085.420 1233.403 1197.230 1124.882 1115.017 1236.692 1216.961
> 1118.305 1078.843
> 101 102 103 104 105 106 107 108
> 109 110
> 1187.364 1141.325 1223.538 1253.135 1161.056 1259.712 1256.423 1269.577
> 1068.977 1147.902
> 111 112 113 114 115 116 117 118
> 119 120
> 1210.384 1131.459 1121.594 1134.748 1207.095 1243.269 1180.787 1088.709
> 1239.981 1164.345
> 121 122 123 124 125 126 127 128
> 129 130
> 1279.443 1082.131 1072.266 1246.558 1266.289 1203.807 1292.597 1272.866
> 1263.000 1249.846
> 131 132
> 1226.826 1305.751
>
>
>
>
> What is this supposed to mean?
>
>
>
> mod1 = lm(sold ~ age + gender)
>
> all.x <- expand.grid(age=unique(age), gender=unique(gender))
>
> y.hat.new <- predict(mod1, newdata=all.x)
> y.hat.new
>
>
>
> On Wed, Dec 21, 2011 at 1:43 AM, Tal Galili <tal.gal...@gmail.com> wrote:
>
>> combind
>> ?predict
>> and:
>> expand.grid(weather=1:2,gender=c("male","female"))
>>
>>
>>
>>
>>
>> ----------------Contact
>> Details:-------------------------------------------------------
>> Contact me: tal.gal...@gmail.com | 972-52-7275845
>> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
>> www.r-statistics.com (English)
>>
>> ----------------------------------------------------------------------------------------------
>>
>>
>>
>>
>> On Wed, Dec 21, 2011 at 6:59 AM, Abraham Mathew <abmathe...@gmail.com>wrote:
>>
>>> Lets say I have a linear model and I want to find the average expented
>>> value of the dependent variable. So let's assume that I'm studying the
>>> price I pay for coffee.
>>>
>>> Price = B0 + B1(weather) + B2(gender) + ...
>>>
>>> What I'm trying to find is the predicted price for every possible
>>> combination of values in the independent variables.
>>>
>>> So Expected price when:
>>> weather=1, gender=male
>>> weather=1, gender=female
>>> weather=2, gender=male
>>> etc.
>>>
>>> Can anyone help with this problem?
>>>
>>> --
>>> *Abraham Mathew
>>> Statistical Analyst
>>> www.amathew.com
>>> 720-648-0108
>>> @abmathewks*
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>
>
>
> --
> *Abraham Mathew
> Statistical Analyst
> www.amathew.com
> 720-648-0108
> @abmathewks*
>
[[alternative HTML version deleted]]
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