query: Fitting power law with loglog or exponential?
positive_passages.docid: 22668
positive_passages.text: Linear vs. nonlinear regression
negative_passages.docid: 158107
negative_passages.text: Joint density for exponential distribution
negative_passages.docid: 45891
negative_passages.text: When (and why) should you take the log of a distribution (of numbers)?
negative_passages.docid: 150792
negative_passages.text: How to electronically generate exponential and logarithmic functions
negative_passages.docid: 102399
negative_passages.text: Computing $ \int_0^\infty \frac{\log x}{\exp x} \ dx $
negative_passages.docid: 68535
negative_passages.text: Finding the distribution of sum of Lognormal Random Variables
negative_passages.docid: 2990
negative_passages.text: How to compute moments of log normal distribution?
negative_passages.docid: 43556
negative_passages.text: How to do exponential and logarithmic curve fitting in Python? I found only polynomial fitting
negative_passages.docid: 73764
negative_passages.text: Fitting exponential (regression) model by MLE?
negative_passages.docid: 42306
negative_passages.text: Motivation for Napier's Logarithms
negative_passages.docid: 91193
negative_passages.text: Natural log approximation
negative_passages.docid: 52094
negative_passages.text: How do I calculate a confidence interval for the mean of a log-normal data set?
negative_passages.docid: 116513
negative_passages.text: Distributional Laplacian of logarithm and the Dirac delta distribution
negative_passages.docid: 148673
negative_passages.text: Comparison of log-likelihood of two non-nested models
negative_passages.docid: 37981
negative_passages.text: How to find normal and lognormal moments, given partial information?
negative_passages.docid: 98886
negative_passages.text: Sampling distribution of exponential sample variance (formal not empirical)
negative_passages.docid: 52154
negative_passages.text: Log-like operator with math inside (e.g. p-lim)