For example, things like interest rates, inflation, and stock prices often influence each other. Standard decision tree models do not inherently account for these interdependencies, potentially ...

"Waiting to be sold: researchers develop model to predict probability of home sales." ScienceDaily. ScienceDaily, 18 March 2017. <www.sciencedaily.com / releases / 2017 / 03 / 170314135449.htm>.

This paper presents a backtesting framework for a probability of default (PD) model, assuming that the latter is calibrated to both point-in-time (PIT) and through-the-cycle (TTC) levels. We claim ...

The point-in-time rating transition probability, for PD term structure for IFRS9 expected credit loss estimation and CCAR stress testing, is estimated by A forward ordinal probability model structured ...

The group elected to use a Markov model, which incorporates pseudo-randomly changing parameters in the modeling system, one example being the SARS-CoV-2 reproduction number.

The measure is in the same spirit as Achen's (1982) "level importance" measure for linear models and thus fills an important gap in logit regression analysis. We show, on the basis of simulations and ...

In this article, we develop a model-free procedure to estimate multiclass probabilities based on large-margin classifiers. In particular, the new estimation scheme is employed by solving a series of ...

For example, if a player is waived out of the face-off due to a violation, the model updates the prediction to the new matchup based on the real-time puck and player tracking streaming sensor data ...