Hi, I'm learning the CUSUMV2 code and I am a bit unsure over where to find the justification for this formula that is used for log-likelihood function:
logp = stepsize*basesd/variance * (data[k] - mean - stepsize*basesd/2.) #instantaneous log-likelihood for current sample assuming local baseline has jumped in the positive direction logn = -stepsize*basesd/variance * (data[k] - mean + stepsize*basesd/2.) #instantaneous log-likelihood for current sample assuming local baseline has jumped in the negative direction
I'd really appreciate anyone that can help me out.
Hi, I'm learning the CUSUMV2 code and I am a bit unsure over where to find the justification for this formula that is used for log-likelihood function:
logp = stepsize*basesd/variance * (data[k] - mean - stepsize*basesd/2.) #instantaneous log-likelihood for current sample assuming local baseline has jumped in the positive direction logn = -stepsize*basesd/variance * (data[k] - mean + stepsize*basesd/2.) #instantaneous log-likelihood for current sample assuming local baseline has jumped in the negative directionI'd really appreciate anyone that can help me out.