Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “regression”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

A regression technique for determining temperature profiles in the upper stratosphere from satellite-measured radiances.

A technique is described whose application makes it possible to almost double the altitude range over which useful temperature profiles may be obtained. For a wide range of atmospheric temperature profiles, the temperature structure between 30 and 55 km may be derived with an expected error of less than 3 C at 30 km to less than 10 C at 55 km, given the temperature structure in the lower 30 km of the profile, and given a consistent and accurate set of radiance observations. For strongly anomalous conditions in the stratosphere, the accuracy of retrievals at tropospheric levels may also be substantially improved.

Gelman, M. E.↗
NASA NTRS1974

Chain pooling to minimize prediction error in subset regression

Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.

Holms, A. G.↗
NASA NTRS1976

Performance of a recoverable tug for planetary missions including use of perigee propulsion and corrections for nodal regression

Mathematical equations are derived by using the Maximum Principle to obtain the maximum payload capability of a reusable tug for planetary missions. The mathematical formulation includes correction for nodal precession of the space shuttle orbit. The tug performs this nodal correction in returning to this precessed orbit. The sample case analyzed represents an inner planet mission as defined by the declination (fixed) and right ascension of the outgoing asymptote and the mission energy. Payload capability is derived for a typical cryogenic tug and the sample case with and without perigee propulsion. Optimal trajectory profiles and some important orbital elements are also discussed.

Borsody, J.↗
NASA NTRS1976

Performance of a recoverable Tug for planetary missions including use of perigee propulsion and corrections for nodal regression

Mathematical equations are derived by using the Maximum Principle to obtain the maximum payload capability of a reusable Tug for planetary missions. The mathematical formulation includes correction for nodal precession of the Space Shuttle orbit. The Tug performs this nodal correction in returning to this precessed orbit. The sample case analyzed represents an inner planet mission as defined by the declination (fixed) and right ascension of the outgoing asymptote and the mission energy. Payload capability is derived for a typical cryogenic Tug and the sample case with and without perigee propulsion. Optimal trajectory profiles and some important orbital elements are also discussed.

Borsody, J.↗
NASA NTRS1976

Linear feedback rate bounds for regressive channels

Bounds for the linear feedback capacity of m-th order Gaussian autoregressive channels are derived. The upper bound is tighter than that found by Tiernan and Schalwijk (1974) for the feedback capacity of a first-order autoregressive Gaussian channel with not necessarily linear processing. The separation between the upper and lower bounds is small, and it is conjectured that the lower bound converges to the feedback capacity of the first-order channel as the number of signals tends to infinity.

Butman, S. A.↗