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| author | Ben Green <bgreen@g.harvard.edu> | 2015-09-13 11:11:10 -0400 |
|---|---|---|
| committer | Ben Green <bgreen@g.harvard.edu> | 2015-09-13 11:11:13 -0400 |
| commit | 754bc37b60d5efbcf0ddad7b991f6effafe2237d (patch) | |
| tree | 42b90919780df34ab0c5465be3ae67238ad60740 | |
| parent | 750ce1282d4604df96ab9a3d676dba448d9d838f (diff) | |
| download | criminal_cascades-754bc37b60d5efbcf0ddad7b991f6effafe2237d.tar.gz | |
changed background model from sin^2 to sin
| -rw-r--r-- | R Scripts/fit-background.R | 8 | ||||
| -rw-r--r-- | hawkes/README.rtf | 13 |
2 files changed, 17 insertions, 4 deletions
diff --git a/R Scripts/fit-background.R b/R Scripts/fit-background.R index d1799cd..73ab6b2 100644 --- a/R Scripts/fit-background.R +++ b/R Scripts/fit-background.R @@ -17,14 +17,14 @@ counts = as.vector(t) infs = data.frame(days,counts) # define background function -fit = function(x, lambda, A, phi) {lambda + A*(sin((pi/365)*x+phi))^2} -fit_form = counts ~ lambda + A*(sin((pi/365)*days+phi))^2 +fit = function(x, lambda, A, phi) {lambda + A*(sin((2*pi/365.24)*x+phi))} +fit_form = counts ~ lambda + A*(sin((2*pi/365.24)*days+phi)) # explore data plot(days,counts) -curve(fit(x, lambda=1, A=12, phi=2.8), add=TRUE ,lwd=2, col="steelblue") +curve(fit(x, lambda=3, A=2, phi=4), add=TRUE ,lwd=4, col="steelblue") -res = nls(formula=fit_form, data=infs, start=list(lambda=1, A=12, phi=2.8)) +res = nls(formula=fit_form, data=infs, start=list(lambda=3, A=2, phi=4)) co = coef(res); co plot(t) diff --git a/hawkes/README.rtf b/hawkes/README.rtf new file mode 100644 index 0000000..be4aff3 --- /dev/null +++ b/hawkes/README.rtf @@ -0,0 +1,13 @@ +{\rtf1\ansi\ansicpg1252\cocoartf1348\cocoasubrtf170 +{\fonttbl\f0\fswiss\fcharset0 Helvetica;} +{\colortbl;\red255\green255\blue255;} +\margl1440\margr1440\vieww10800\viewh8400\viewkind0 +\pard\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\pardirnatural + +\f0\fs24 \cf0 \ +\ +data/data2 - reformatting the data files\ +\ +main - most of the optimization\ +\ +cause - assign responsibility for each infection}
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