Hi:
I am sorry for beginner question. I have never used spline regression in Stata, so it is a bit of new for me how to run spline regression on those temperature bins data down below. I just got a very basic idea of spline regression model, but in terms of environmental economic setting, I have a little idea how should I run spline regression on that. Can anyone give me a possible lead or general spline regression strategy for bins temperature data? Or any reference Stata command that allows me to see how spline regression works on temperature bins data? Thanks in advance and sorry if my question is too easy for you!
Here is example snippet temperature bin data:
I am sorry for beginner question. I have never used spline regression in Stata, so it is a bit of new for me how to run spline regression on those temperature bins data down below. I just got a very basic idea of spline regression model, but in terms of environmental economic setting, I have a little idea how should I run spline regression on that. Can anyone give me a possible lead or general spline regression strategy for bins temperature data? Or any reference Stata command that allows me to see how spline regression works on temperature bins data? Thanks in advance and sorry if my question is too easy for you!
Here is example snippet temperature bin data:
Code:
1980 9 6 20 23 31 42 38 21 36 44 41 26 18 8 3 1981 5 12 27 26 23 35 23 26 30 48 39 37 19 8 7 1982 9 2 14 21 28 38 33 35 33 29 38 34 22 18 11 1983 5 12 10 19 32 32 32 36 43 29 39 19 23 18 16 1984 0 5 10 26 47 42 31 23 46 50 42 20 14 6 4 1985 28 12 14 23 27 28 30 21 36 37 47 35 16 9 2 1986 20 10 13 22 23 33 24 46 37 50 22 23 20 16 6 1987 23 10 21 23 22 17 35 37 43 31 48 26 16 9 4 1988 0 1 3 21 32 49 45 29 29 44 48 38 17 8 2 1989 0 3 11 13 37 35 36 47 31 34 34 31 33 11 9 1990 0 0 5 21 21 39 45 36 47 43 39 29 18 13 9 1991 8 8 20 17 28 40 32 38 37 45 26 30 19 7 10 1992 6 4 10 6 29 54 50 33 32 17 31 33 30 23 8 1993 7 8 25 16 28 32 36 29 32 39 45 32 26 10 0 1994 5 5 6 10 31 34 37 46 36 42 41 22 13 17 20
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