How do I structure data to use R lmer -


I am trying to analyze the reliability data, a specific case should be determined that the specified plants on specified plants Whether the demand rate for 10-year trend is present or not.

I am trying to generate a test case, but there is a bit confused about how to structure the data. The trend is happening from 2004 to 2013. In my trial, I have 10 systems each year for which the demands have been calculated. I usually calculate the distribution with different methods and variations each year. Of course, the probability of real data will not be calculated the same system every year, and the demand count is not necessarily distributed normally.

The following R code generates a data frame (DF1) that I think is appropriate:

  yr < - 2004: 2013 y2004 & lt; - rnorm (10, 10), 3) y2005 & lt; - rnorm (10, 11, 2) y2006 & lt; - rnorm (10, 12, 1) y2007 & lt; - rnorm (10, 13, 5) y2008 & lt; - rnorm (10, 14, 3) Y2009 & lt; - rnorm (10, 15, 4) y2010 & lt; - rnorm (10, 16, 1) y2011 & lt; - rnorm (10, 17, 2) y2012 & lt; - rnorm (10, 18, 4) y2013 & lt; - rnorm (10, 19, 1) df1 & lt; - data.fr (cbind (yr), y2004, y2005, y2006, y2007, y2008, y2009, y2010, y2011, y2012, y2013) df2 & lt; - Data C ("X", "Y") for K-1 (i.e. in 1:10) (cbind (Representative (0.0, 100), Representative (0.0, 100)) Name (DF2) & Lt; - for c (in 1:10) {df2 $ x [k] & lt; - df1 $ yr [i] df2 $ y [k] & lt; - df1 [j, i + 1] k & lt; - k + 1}} Anyway, my first problem is the creation of Df2 seems unnecessary I already have data in df1 - it is just that the call to lmer requires the call of the DF 2 lmer for the following call Looks like:  
  Fit  

So what is a way to use lmer without df2, directly using DF1 ? Or is there a better way to fully structate data?

My second problem is that I am not really sure what I want to do. Basically I'm looking to pool the counting data for each year and calculate the average demand from a straight line every year. The best fit should consider the difference in each pool year group data. Am I going about this right? In R almost all conspiracy and modeling functions require data in the "long" format (i.e

). So if anything, I will skip the construction of df1 . If you want to generate more df2 more directly, you can

  df2 & lt; - do.call ("rbind.data.frame", map (cbind, y) = map (function (n, m, s) rnorm (n, m, s), 10, 10:19, c (3,2) , 1,5,3,4,1,2,3,1)), X = 2004: 2013))  

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