The contribution is focused on change point detection in a one-dimensional stochastic process by sparse parameter estimation from an overparametrized model. A stochastic process with change in the mean is estimated using dictionary consisting of Heaviside functions. The basis pursuit algorithm is used to get sparse parameter estimates. The mentioned method of change point detection in a stochas...

Existing methods for bar code signal reconstruction is based on either the local approach or the regularization approach with total variation penalty. We formulate the problem explicitly in terms of change points of the 0-1 step function. The bar code is then reconstructed by solving the nonlinear least squares problem subject to linear inequality constraints, with starting values provided by t...

We study change–point estimation using a two–stage (generalizable to multi–stage) sampling design in a regression setting Y = f(X) + 2. For the talk, the underlying regression function is assumed to be parametrically specified, with a single unknown jump discontinuity of interest. The experimenter is given a budget of n points to make inference on the change–point. The two–stage procedure works...

We develop a method of estimating change{points of a function in the case of indirect noisy observations. As two paradigmatic problems we consider de-convolution and errors-in-variables regression. We estimate the scalar products of our indirectly observed function with appropriate test functions, which are shifted over the interval of interest. An estimator of the change point is obtained by t...

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where ...

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Reconstruction of a bilevel function such as a bar code signal in a partially blind deconvolution problem is an important task in industrial processes. Existing methods are based on either the local approach or the regularization approach with a total variation penalty. This article reformulated the problem explicitly in terms of change points of the 0-1 step function. The bilevel function is t...