Description Usage Arguments Value Functions See Also
View source: R/tweetfunctions.R
Integration with respect to locally weighted kernel
1 2 3 4 5 6 7  linear.kernel(t1, t2, ptime, slope, c = 0.0006265725)
power.kernel(t1, t2, ptime, share.time, slope, theta = 0.2314843,
cutoff = 300, c = 0.0006265725)
integral.memory.kernel(p.time, share.time, slope, window, theta = 0.2314843,
cutoff = 300, c = 0.0006265725)

t1 
a vector of integral lower limit 
t2 
a vector of integral upper limit 
ptime 
the time (a scalar) to estimate infectiousness and predict for popularity 
slope 
slope of the linear kernel 
c 
the constant density when t is less than the cutoff 
share.time 
observed resharing times, sorted, share.time[1] =0 
theta 
exponent of the power law 
cutoff 
the cutoff value where the density changes from constant to power law 
p.time 
equally spaced vector of time to estimate the infectiousness, p.time[1]=0 
window 
size of the linear kernel 
linear.kernel
returns the integral from vector t1 to vector t2 of
c*[slope(tptime) + 1];
power.kernel
returns the integral from vector t1 to vector 2 of c*((tshare.time)/cutoff)^((1+theta))[slope(tptime) + 1];
integral.memory.kernel
returns the vector with ith entry being integral_inf^inf phi_share.time[i]*kernel(tp.time)
power.kernel
:
integral.memory.kernel
:
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