Sunday, September 5, 2010

JS-Blogger-Client: R-server Post

{
    "Histogram of Auto Sales": {
        "value": "SCRPT-fe241889-f9f1-492e-9648-318d5710b2e8"
    },
    "plotsales-png": {
        "value": "SCRPT-9ce8f7f3-d45b-498f-a107-6c6de91c43d7"
    },
    "psycolv2": {
        "value": "SCRPT-541a3335-2a36-4816-94a9-ded759fc1df4"
    },
    "masked_figure1": {
        "value": "SCRPT-72240b50-90e5-45af-9770-71859abfe416"
    },
    "segmented_regression": {
        "value": "SCRPT-8903ea9f-bcd2-4f79-acbd-f8418dc03df5"
    },
    "runsource": {
        "value": "SCRPT-0b6cbeda-760d-4076-a0ec-119b6507c3d2"
    },
    "segreg_test": {
        "value": "SCRPT-2cf16ca5-973a-49ce-bfb6-607bd0972e81"
    }
}

{
    "submited": "Mon Sep 06 2010 02:42:53 GMT+0200 (W. Europe Daylight Time)",
    "scriptname": "runsource",
    "inputs": {
        "sourcescript": "/home/garyfeng/segreg_test.r",
        "sourcedata": "/home/garyfeng/allfix.RData",
        "salesforecast": "1",
        "saleserrorbar": "0",
        "charts": {
            "hazfunc": false,
            "bk1": 36,
            "bk2": 50
        },
        "displaysize": {
            "width": 675,
            "height": 785
        }
    },
    "files": ["output.png"]
}

Results

time = Mon Sep 06 2010 02:43:07 GMT+0200 (W. Europe Daylight Time)

Console output

{
    "value": "$time
[1] 3.0 5.0 6.5 7.5 12.0 18.0 22.0 26.0 30.0 34.0 38.0 42.0
[13] 46.0 50.0 54.0 58.0 62.0 66.0 70.0 74.0 78.0 82.0 86.0 90.0
[25] 94.0 98.0 102.0 106.0 110.0 114.0 118.0 122.0 126.0 130.0 134.0 138.0
[37] 142.0 146.0 150.0 154.0 158.0 162.0 166.0 170.0 174.0 178.0 182.0 186.0
[49] 190.0 194.0 198.0 202.0 206.0 210.0 214.0 218.0 222.0 226.0 230.0 234.0
[61] 238.0 242.0 246.0 250.0 254.0 258.0 262.0 266.0 270.0 274.0 278.0 282.0
[73] 286.0 290.0 294.0 298.0 302.0 306.0 310.0 314.0 318.0 322.0 326.0 330.0
[85] 334.0 338.0 342.0 346.0 350.0 354.0 358.0 362.0 366.0 370.0 374.0 378.0
[97] 382.0 386.0 390.0 394.0 398.0 402.0 406.0 410.0 414.0 418.0 422.0 426.0
[109] 430.0 434.0 438.0 442.0 446.0 450.0 454.0 458.0 462.0 466.0 470.0 474.0
[121] 478.0 482.0 486.0 490.0 494.0 498.0 502.0 506.0 510.0 514.0 518.0 522.0
[133] 526.0 530.0 534.0 538.0 542.0 546.0 550.0 554.0 558.0 562.0 566.0 570.0
[145] 574.0 578.0 582.0 586.0 590.0 594.0 598.0 602.0 606.0 610.0 614.0 618.0
[157] 622.0 626.0 630.0 634.0 638.0 642.0 646.0 650.0 654.0 658.0 662.0 666.0
[169] 670.0 674.0 678.0 682.0 686.0 690.0 694.0 698.0 704.0 710.0 714.0 718.0
[181] 722.0 726.0 730.0 734.0 738.0 742.0 746.0 750.0 754.0 758.0 762.0 766.0
[193] 770.0 774.0 778.0 782.0 786.0 790.0 794.0 798.0 802.0 808.0 814.0 828.0
[205] 842.0 846.0 852.0 858.0 862.0 866.0 874.0 886.0 900.0 910.0 914.0 920.0
[217] 930.0 940.0 948.0

$haz
[1] 6.000780e-05 1.300416e-04 4.001881e-05 1.400784e-04 2.501601e-06
[6] 6.004624e-05 7.007217e-05 4.559485e-04 5.723641e-04 3.722372e-04
[11] 5.341721e-04 7.275010e-04 8.209772e-04 7.880347e-04 1.066524e-03
[16] 8.965357e-04 1.322482e-03 1.433277e-03 1.566832e-03 1.781735e-03
[21] 1.842202e-03 2.074811e-03 2.356280e-03 2.427703e-03 2.946914e-03
[26] 2.909587e-03 3.406797e-03 3.602876e-03 3.574129e-03 4.411965e-03
[31] 4.153980e-03 4.634599e-03 4.884636e-03 5.122328e-03 5.588123e-03
[36] 5.742599e-03 6.521021e-03 7.555988e-03 7.747776e-03 8.070830e-03
[41] 7.920304e-03 8.814306e-03 9.729716e-03 9.158689e-03 9.353825e-03
[46] 8.941314e-03 9.234247e-03 9.900719e-03 9.219054e-03 9.604677e-03
[51] 1.031669e-02 1.024113e-02 9.597369e-03 1.017204e-02 1.137747e-02
[56] 9.812395e-03 1.125798e-02 1.139298e-02 1.177751e-02 1.269532e-02
[61] 1.227937e-02 1.352709e-02 1.286691e-02 1.418649e-02 1.365680e-02
[66] 1.405206e-02 1.415270e-02 1.521055e-02 1.398254e-02 1.349920e-02
[71] 1.581401e-02 1.444180e-02 1.383152e-02 1.390733e-02 1.290536e-02
[76] 1.356722e-02 1.288233e-02 1.358239e-02 1.273628e-02 1.437798e-02
[81] 1.221396e-02 1.446594e-02 1.333111e-02 1.264400e-02 1.115687e-02
[86] 1.270497e-02 1.534701e-02 1.172206e-02 1.093754e-02 1.127089e-02
[91] 1.338457e-02 7.787955e-03 1.011270e-02 1.212418e-02 1.159451e-02
[96] 1.063311e-02 9.746528e-03 1.108471e-02 1.321199e-02 9.255621e-03
[101] 9.611505e-03 1.224117e-02 1.036119e-02 9.127285e-03 1.201854e-02
[106] 1.061557e-02 8.311484e-03 1.165054e-02 1.165152e-02 1.122914e-02
[111] 1.258894e-02 1.237982e-02 6.652277e-03 7.296459e-03 1.233062e-02
[116] 1.093070e-02 1.089949e-02 1.278842e-02 9.967150e-03 8.871421e-03
[121] 7.641181e-03 1.110589e-02 1.401301e-02 8.374822e-03 1.087916e-02
[126] 9.057593e-03 7.807034e-03 8.468550e-03 8.765504e-03 1.218692e-02
[131] 1.001043e-02 3.271074e-03 8.126908e-03 1.092527e-02 6.166806e-03
[136] 6.322779e-03 8.687081e-03 8.999843e-03 8.149728e-03 1.274547e-02
[141] 9.518911e-03 5.228946e-03 4.666799e-03 2.706385e-03 9.709952e-03
[146] 1.010238e-02 5.961530e-03 6.107169e-03 1.025379e-02 9.853483e-03
[151] 1.113197e-02 9.822682e-03 7.394246e-03 7.619628e-03 1.087126e-02
[156] 9.260305e-03 7.447348e-03 1.082251e-03 4.376472e-03 7.848165e-03
[161] 5.760613e-03 1.168224e-03 7.126360e-03 1.108554e-02 1.693352e-02
[166] 1.102104e-02 5.698237e-03 1.180157e-02 3.039542e-03 4.629747e-03
[171] 1.562500e-03 4.746962e-03 1.602564e-03 1.661735e-02 1.596280e-02
[176] 3.690087e-03 5.704384e-03 7.905756e-03 1.024728e-02 4.219484e-03
[181] 1.535560e-02 4.566305e-03 4.651263e-03 7.143289e-03 9.853412e-03
[186] 5.076273e-03 7.813065e-03 5.347747e-03 1.105141e-02 5.714472e-03
[191] 5.848153e-03 9.037019e-03 1.258110e-02 3.246753e-03 1.000119e-02
[196] 6.896880e-03 3.521127e-03 3.571429e-03 3.623188e-03 1.863908e-01
[201] 1.587702e-02 1.294130e-02 1.887464e-02 1.666667e-03 5.705463e-02
[206] 2.704678e-02 2.349877e-02 1.785714e-02 1.923077e-02 4.356061e-02
[211] 8.333333e-03 9.259259e-03 1.674107e-02 4.166667e-02 5.000000e-02
[216] 3.125000e-02 2.777778e-02 6.250000e-02 1.250000e-01

$var
[1] 6.001560e-10 1.300832e-09 8.007525e-10 2.803139e-09 6.258008e-12
[6] 3.004625e-10 3.507221e-10 2.284496e-09 2.873691e-09 1.872440e-09
[11] 2.691886e-09 3.675404e-09 4.160519e-09 4.006447e-09 5.442465e-09
[16] 4.593012e-09 6.805304e-09 7.416200e-09 8.156050e-09 9.337043e-09
[21] 9.724142e-09 1.103812e-08 1.264715e-08 1.315578e-08 1.614201e-08
[26] 1.612532e-08 1.912099e-08 2.050702e-08 2.063750e-08 2.588556e-08
[31] 2.479303e-08 2.815219e-08 3.024136e-08 3.235408e-08 3.606052e-08
[36] 3.790678e-08 4.411423e-08 5.257579e-08 5.558596e-08 5.976509e-08
[41] 6.055643e-08 6.968614e-08 7.983080e-08 7.803811e-08 8.270723e-08
[46] 8.200576e-08 8.782803e-08 9.784136e-08 9.465543e-08 1.023986e-07
[51] 1.144615e-07 1.183921e-07 1.154396e-07 1.272874e-07 1.486443e-07
[56] 1.337437e-07 1.600549e-07 1.694811e-07 1.835125e-07 2.077396e-07
[61] 2.112230e-07 2.450157e-07 2.456882e-07 2.859524e-07 2.910367e-07
[66] 3.165261e-07 3.372936e-07 3.844389e-07 3.746407e-07 3.821233e-07
[71] 4.746987e-07 4.605378e-07 4.667311e-07 4.960607e-07 4.856716e-07
[76] 5.383470e-07 5.389327e-07 5.991126e-07 5.921456e-07 7.057451e-07
[81] 6.322476e-07 7.898939e-07 7.695260e-07 7.687728e-07 7.114086e-07
[86] 8.497417e-07 1.085736e-06 8.753627e-07 8.546340e-07 9.206853e-07
[91] 1.148650e-06 6.972086e-07 9.383538e-07 1.176196e-06 1.179446e-06
[96] 1.130802e-06 1.079623e-06 1.280113e-06 1.601811e-06 1.173648e-06
[101] 1.265649e-06 1.684002e-06 1.491246e-06 1.365846e-06 1.876275e-06
[106] 1.733958e-06 1.409941e-06 2.056963e-06 2.155276e-06 2.174394e-06
[111] 2.556690e-06 2.642954e-06 1.475180e-06 1.663815e-06 2.924517e-06
[116] 2.715892e-06 2.828995e-06 3.480413e-06 2.838778e-06 2.623678e-06
[121] 2.335687e-06 3.524599e-06 4.676564e-06 2.922675e-06 3.945827e-06
[126] 3.418706e-06 3.047736e-06 3.415389e-06 3.659138e-06 5.305369e-06
[131] 4.555552e-06 1.528582e-06 3.885437e-06 5.426386e-06 3.169284e-06
[136] 3.331638e-06 4.717059e-06 5.062868e-06 4.744566e-06 7.737246e-06
[141] 6.041371e-06 3.417857e-06 3.111377e-06 1.831146e-06 6.735354e-06
[146] 7.290846e-06 4.442687e-06 4.662418e-06 8.088843e-06 8.091968e-06
[151] 9.533923e-06 8.772489e-06 6.834850e-06 7.257895e-06 1.074571e-05
[156] 9.529214e-06 7.923859e-06 1.171267e-06 4.788492e-06 8.799807e-06
[161] 6.637215e-06 1.364748e-06 8.464725e-06 1.365656e-05 2.206561e-05
[166] 1.518534e-05 8.117806e-06 1.741281e-05 4.619450e-06 7.145035e-06
[171] 2.441406e-06 7.511417e-06 2.568212e-06 2.762370e-05 2.832184e-05
[176] 6.808464e-06 5.424249e-06 1.562646e-05 2.100417e-05 8.902183e-06
[181] 3.369532e-05 1.042579e-05 1.081736e-05 1.700989e-05 2.427538e-05
[186] 1.288461e-05 2.034947e-05 1.429961e-05 3.053808e-05 1.632813e-05
[191] 1.710103e-05 2.722521e-05 3.957888e-05 1.054141e-05 3.334519e-05
[196] 2.378461e-05 1.239833e-05 1.275510e-05 1.312749e-05 1.010533e-03
[201] 1.260716e-04 5.587003e-05 1.781895e-04 2.777778e-06 6.537600e-04
[206] 3.660314e-04 1.845453e-04 3.188776e-04 3.698225e-04 9.505567e-04
[211] 6.944444e-05 8.573388e-05 1.407545e-04 1.736111e-03 2.500000e-03
[216] 9.765625e-04 7.716049e-04 3.906250e-03 1.562500e-02

No traceback available
"
}

Figure

plot

{
    "submited": "Mon Sep 06 2010 02:43:25 GMT+0200 (W. Europe Daylight Time)",
    "scriptname": "runsource",
    "inputs": {
        "sourcescript": "/home/garyfeng/Potsdam/1.ANOVA.R",
        "sourcedata": "/home/garyfeng/Potsdam/MaskedPriming.rda",
        "salesforecast": "1",
        "saleserrorbar": "0",
        "charts": {
            "hazfunc": false,
            "bk1": 36,
            "bk2": 50
        },
        "displaysize": {
            "width": 675,
            "height": 785
        }
    },
    "files": ["output.png"]
}

Results

time = Mon Sep 06 2010 02:43:37 GMT+0200 (W. Europe Daylight Time)

Console output

{
    "value": "
Error: subjects
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
e         2 2.9864 1.49319 45.684 2.311e-13 ***
Residuals 69 2.2553 0.03269                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: subjects:f
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
f         1 1.28900 1.28900 314.519 < 2.2e-16 ***
e:f       &nbsp2 0.32395 0.16198 39.523 3.645e-12 ***
Residuals 69 0.28279 0.00410                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: subjects:p
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
p         1 0.191056 0.191056 95.3156 1.242e-14 ***
e:p       &nbsp2 0.020121 0.010061 5.0191 0.009224 **
Residuals 69 0.138308 0.002004                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: subjects:f:p
         Df Sum Sq Mean Sq F value Pr(>F)
f:p       &nbsp1 0.005810 0.0058101 5.5015 0.02188 *
e:f:p     2 0.001116 0.0005582 0.5286 0.59181
Residuals 69 0.072871 0.0010561                
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: words
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
f         1 3.7438 3.7438 117.75 < 2.2e-16 ***
Residuals 94 2.9886 0.0318                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: words:e
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
e         1 0.56448 0.56448 48.5825 4.321e-10 ***
f:e       &nbsp1 0.00086 0.00086 0.0738   &nbsp0.7865    
Residuals 94 1.09218 0.01162                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: words:p
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
p         1 0.34788 0.34788 40.1447 8.076e-09 ***
f:p       &nbsp1 0.00517 0.00517 0.5969   &nbsp0.4417    
Residuals 94 0.81458 0.00867                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: words:e:p
         Df Sum Sq Mean Sq F value Pr(>F)
e:p       &nbsp1 0.06952 0.069524 10.3729 0.001757 **
f:e:p     1 0.00151 0.001507 0.2248 0.636518
Residuals 94 0.63003 0.006702                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: words
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
f         1 0.07429 0.074293 19.547 2.633e-05 ***
Residuals 94 0.35727 0.003801                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1

Error: words:p
         Df Sum Sq Mean Sq F value   &nbspPr(>F)    
p         1 0.090752 0.090752 51.2271 1.792e-10 ***
f:p       &nbsp1 0.009661 0.009661 5.4533 0.02166 *
Residuals 94 0.166527 0.001772                    
---
Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1
"
}

Figure

plot

{
    "submited": "Mon Sep 06 2010 02:44:13 GMT+0200 (W. Europe Daylight Time)",
    "scriptname": "runsource",
    "inputs": {
        "sourcescript": "/home/garyfeng/Potsdam/2.Figure1.R",
        "sourcedata": "/home/garyfeng/Potsdam/MaskedPriming.rda",
        "salesforecast": "1",
        "saleserrorbar": "0",
        "charts": {
            "hazfunc": false,
            "bk1": 36,
            "bk2": 50
        },
        "displaysize": {
            "width": 675,
            "height": 785
        }
    },
    "files": ["output.png"]
}

Results

time = Mon Sep 06 2010 02:44:30 GMT+0200 (W. Europe Daylight Time)

Console output

{
    "value": ""
}

Figure

plot

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