# Bounds for the cumulative conditional expectation function

## Abstract

We introduce the concept of cumulative conditional expectation function. This is a quantity that provides statistical support for making decisions in applied problems. The goal of this paper is to find an analytical expression for upper and lower bounds of this function, assuming stochastic dependence types as being the underlying random structure.

- Authors:

- University of Campinas (Brazil)

- Publication Date:

- OSTI Identifier:
- 22391045

- Resource Type:
- Journal Article

- Resource Relation:
- Journal Name: AIP Conference Proceedings; Journal Volume: 1648; Journal Issue: 1; Conference: ICNAAM-2014: International Conference on Numerical Analysis and Applied Mathematics 2014, Rhodes (Greece), 22-28 Sep 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ANALYTICAL SOLUTION; FUNCTIONS; LIMITING VALUES; RANDOMNESS; STOCHASTIC PROCESSES

### Citation Formats

```
Fernández, M., and González-López, V. A.
```*Bounds for the cumulative conditional expectation function*. United States: N. p., 2015.
Web. doi:10.1063/1.4912372.

```
Fernández, M., & González-López, V. A.
```*Bounds for the cumulative conditional expectation function*. United States. doi:10.1063/1.4912372.

```
Fernández, M., and González-López, V. A. Tue .
"Bounds for the cumulative conditional expectation function". United States.
doi:10.1063/1.4912372.
```

```
@article{osti_22391045,
```

title = {Bounds for the cumulative conditional expectation function},

author = {Fernández, M. and González-López, V. A.},

abstractNote = {We introduce the concept of cumulative conditional expectation function. This is a quantity that provides statistical support for making decisions in applied problems. The goal of this paper is to find an analytical expression for upper and lower bounds of this function, assuming stochastic dependence types as being the underlying random structure.},

doi = {10.1063/1.4912372},

journal = {AIP Conference Proceedings},

number = 1,

volume = 1648,

place = {United States},

year = {Tue Mar 10 00:00:00 EDT 2015},

month = {Tue Mar 10 00:00:00 EDT 2015}

}

DOI: 10.1063/1.4912372

Other availability

Save to My Library

You must Sign In or Create an Account in order to save documents to your library.