In the linear calibration problem, when the regression variable y is related to the independent variable x by the equation y=α +β x+σ e, likelihood methods are used to make inferences about an unknown ...

This paper considers linear regression models when neither the response variable nor the covariates can be directly observed, but are measured with multiplicative distortion measurement errors. To ...

The paper presents a Bayesian framework for the calibration of financial models using neural stochastic differential equations (neural SDEs), for which we also formulate a global universal ...