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POHow to use linear models to obtain coefficients by factors levels?
 

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  1. POHow to use linear models to obtain coefficients by factors levels?
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    <p>I'm analyzing data from a solar power plant. I wanted to adjust the estimated production plant Hourly each subsequent day, the data that can be obtained are the weather forecasts of the next three days, so that tomorrow you know what kind of day will be (in scale of 1 to 5, with 1 being sunny and 5 cloudy).</p> <p>So the idea is to multiply the capacity by a factor, so this is an estimate of what will occur and does not deviate from the actual measurement.</p> <p>I figured that establishing a linear model by using the varibale type of day as a factor. Could be the best way to approximate the real production.</p> <p>Today the criteria is:</p> <ul> <li>Day type 1, prodcution capacity*1 </li> <li>Day type 2, prodcution capacity*0.7</li> <li>Day type 3, prodcution capacity*0.4</li> <li>Day type 4, prodcution capacity*0.15</li> <li>Day type 5, prodcution capacity*0</li> </ul> <p>I made a study of these coefficients and the production of the plant is being underestimated, meaning that there is actually more energy produced, almost 50%. Using solver of excel to find the coeffcient I get:</p> <ul> <li>1.6</li> <li>1.2</li> <li>0.9</li> <li>0.65</li> <li>0.5</li> </ul> <p>The trouble is that this is only for this particular case of data and I can not generalize, for it I wanted to make the model).</p> <p><a href="https://www.dropbox.com/s/uds1nl62670pd0i/zcinco.txt" rel="nofollow">data</a></p> <p>This is what I have apply:</p> <pre><code>data &lt;-read.table ("zcinco.txt", dec = ",", header = TRUE) head (data) model &lt;- lm (data [-1.2] ~ embed (data [, 2], 2) [, 2] + as.factor (data [-1.3]) + data [1, 4]) head (cbind (matrix (predict (model)), data [-1.2])) summary (model) Call: lm(formula = data[-1, 2] ~ embed(data[, 2], 2)[, 2] + as.factor(data[-1, 3]) + data[-1, 4]) Residuals: Min 1Q Median 3Q Max -0.054966 -0.009518 -0.000855 0.010966 0.039100 Coefficients: Estimate Std. Error t value Pr(&gt;|t|) (Intercept) 2.528e-06 1.456e-03 0.002 0.9986 embed(data[, 2], 2)[, 2] 3.870e-01 2.969e-02 13.036 &lt; 2e-16 *** as.factor(data[-1, 3])2 -2.630e-03 1.407e-03 -1.869 0.0621 . as.factor(data[-1, 3])3 1.690e-03 2.371e-03 0.713 0.4762 as.factor(data[-1, 3])4 -1.855e-02 2.251e-03 -8.241 1.07e-15 *** as.factor(data[-1, 3])5 -1.790e-02 2.660e-03 -6.727 4.06e-11 *** data[-1, 4] 8.930e-01 4.823e-02 18.517 &lt; 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.01482 on 600 degrees of freedom Multiple R-squared: 0.795, Adjusted R-squared: 0.793 F-statistic: 387.9 on 6 and 600 DF, p-value: &lt; 2.2e-16 </code></pre> <p>Description of the base.</p> <p>tiempo / real / tipo / capacidad</p> <ul> <li>Tiempo: indicates the time of day at which the observation was taken.</li> <li>Real measurement indicates actual energy production.</li> <li>Tipo: indicates the type of day it was in observation (1 to 5).</li> <li>Capacidad: the percentage of estimated production capacity of the plan</li> </ul>
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    1. USMichelle
    1. USMichelle
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    1. COIf I understand correctly what you are trying to do you may need this formula " real ~ tipos:capacidad" which considers an interaction between the factor "tipos" and the capacity and will estimate a coefficient for every combinations of the factor levels and the capacity.
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      1. POHow to use linear models to obtain coefficients by factors levels?
      1. USvodka
    2. COYou totally get what I was trying to do. `model <- lm (real ~ tipos:capacidad)` this is what you are proposing?
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      1. POHow to use linear models to obtain coefficients by factors levels?
      1. USMichelle
    3. COThen try: `data$type <- as.factor(data$tipo)` and then `model2 <- lm(formula="real ~ type:capacidad", data=data)`
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      1. POHow to use linear models to obtain coefficients by factors levels?
      1. USvodka
 

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