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Dear All, I am fitting a simple GAM model using the "gam" function in the "mgcv" package. The only independent variable is a continuous variable representing the time of the event (in year and month) coded so that "0" represents January 1960, "1" represents February 1960, etc. Now when I try to plot the results, my x-axis ranges from "-200" to

Hi, Looking for a function in R that can help me calculate a parameter that maximizes the likelihood over groups of observations. The general formula is: p = exp(xb) / sum(exp(xb)) So, according to the formulas I've seen published, to do this "by group" is product(p = exp(x_i * b_i) / sum(exp(x_i b_i))) Where i represents a "group" and we iterate through each group.

Here''s the problem I have the following models User - is a person Team - is a team Wherenote - snipet of info about a user''s whereabouts on a certain day Team has_and_belongs_to_many :users User has_and_belongs_to_many :teams has_many :wherenotes Wherenote belongs_to :user each Wherenote has a note_date On one page I want to pull back all the Users from a particular Team

Hi, I'm a newbie to R. My knowledge of statistics is mostly self-taught. My problem is how to measure the effect of users in groups. I can calculate a particular attribute for a user in a group. But my hypothesis is that the user's attribute is not independent of each other and that the user's attribute depends on the group ie that user's behaviour change based on the group. Let

Hi, I have a data.frame SAMPLES with columns: Site Site# Season Day1 Day2 Day3 Day1, Day2, Day3 are class "Date", the other columns are numeric or factor. I have a date "mydate" that may or may not be listed in my data.frame and I need to find that out. If "mydate" is there, I want to get the number of the data.frame row where it occurs.

Hi everyone, I'm fairly new to R, and I don't have a background in statistics, so please bear with me. ;-) I'm dealing with 2^k factorial designs, and I was just wondering if there's any way to analyze more than two factors of a gage R&R study in R. For example, Minitab has an "expanded gage R&R" function that lets you include up to eight additional factors

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