coefficients

I have 365 columns. In each column I have 60 values. I need to know the rate of change over time for each column (slope or linear coefficient). I created a generic column as a series of numbers from 1:60 to represent the 60 corresponding time intervals. I want to create 356 linear regression models using the generic time stamp column with each of the 365 columns of data. In other words, I have many columns and I would like to create many linear regression models at once, extract the coefficients and put those coefficients into a new matrix. First of all, statistically this might not be the

How could I extract coefficients (b0 and b1) with their respectively standard errors for each experimental unit (plot )in a linear mixed model such as this one: Better fits for a linear model with this same dataset(df), and for the fitted model (fitL1): how could I get a data frame as this one... plot b0 b0_se b1 b1_se 1 2898.69 53.85 -7.5 4.3 ... ... ... ... ... The first comment is that this is actually a non-trivial theoretical question: there is a rather long thread on r-sig-mixed-models that goes into some of the technical details; you should definitely have a look, even though it gets a