We present a new maximum likelihood method for the calculation of galaxy luminosity functions from multi-band photometric surveys without spectroscopic data. The method evaluates the likelihood of a ...

Abstract: Given a relative maximum of the log-likelihood function, how to assess whether it is the global maximum? This paper investigates a statistical tool, which answers this question by posing it ...

The need to combine likelihood information is common in analyses of complex models and in meta-analyses, where information is combined from several studies. We work to first order, and show that full ...

1 Cornell Center for Astrophysics and Planetary Science (CCAPS) and Department of Statistics and Data Science, Cornell University, Ithaca, NY, United States 2 Department of Statistical Science, Duke ...

A solar physicist who accurately predicted that the sun's explosive peak would arrive sooner — and be more powerful — than originally forecast tells Live Science that it may have already begun.

A transformational measurement model for structural equation modeling (SEM) of asymmetric non-normal data is proposed. This measurement model aligns with the expectation-maximization (EM) algorithm of ...

Here for a small dataset we have used OLS(Ordiniary Least Square) and MLE(Maximum likelihood Estimation ) to calculate the regression parameters slope(b1),intercept(b0) and standard deviation of ...

The maximum likelihoood estimator approach is used here for calculating the Regression parameter that is slope(b1),intercept(b0) and standard deviation of error/residuals. Then Result or the output ...

Diagram of MURAL, our method for learning uncertainty-aware rewards for RL. After the user provides a few examples of desired outcomes, MURAL automatically infers a reward function that takes into ...