Tightness and exponential tightness of Gaussian probabilities

2020/01/08 by Baldi, Paolo · 1 citation
#60B12 #60F10 #FOS: Mathematics #Probability (math.PR)

paper · doi:10.48550/arxiv.2001.02516

Abstract

We prove a simple criterion of exponential tightness for sequences of Gaussian r.v.'s with values in a separable Banach space from which we deduce a general result of Large Deviations which allows easily to obtain LD estimates in various situations.

Cited by

• LDP for the covariance process in fully connected neural networks

Related

• Intermediate spaces, Gaussian probabilities and exponential tightness
• More on the convergence of Gaussian convex hulls
• Sufficient conditions for exponential tightness of normed sums of independent random fields in the space of continuous functions
• Large deviation principle for stochastic integrals and stochastic\n differential equations driven by infinite-dimensional semimartingales
• Tightness conditions for polymer measures