Component Factors of the Time-Series Model Smoothing of Data Series Moving Averages Exponential Smoothing Least Square Trend Fitting and Forecasting Linear, Quadratic and Exponential Models Autoregressive Models Choosing Appropriate Models Monthly or Quarterly Data
In order to be able to design a robust compensator to control a given pro cess, it is necessary not only to specify a nominal mo del of the process, but also the model uncert ainty to which the control sy stem has to be robust. The compensator is required to make the output follow variations in the reference signal and to attenuate disturbances. Hence to design the com- pensator
Collaborate Document Management Plan and design up front Create a short model section for information content and order Create a layout template Create a document control system for revisions Accept individual responsibility and deadlines
For contact information about worldwide offices, see the Math Works Web site. Writing S-Functions COPYRIGHT 1998-2002 by The Math Works, Inc. The software described in this document is fur d under a license agreement. The software may be used or copied only under the terms of the license agreement. No part of this manual may be photocopied or repro-
The software described in this document is furnished under license agreement. The software may be used or copied only under the terms of the license agreement. No part of this manual may be photocopied or repro- duced in any form without prior written consent from The Math Works. In FEDERAL ACQUiSITION to all acquisitions of the Program and Documentation by or for the federal
COPYRIGHT 1998-2002 by The Math Works, Inc. The software described in this document is fur d under a license agreement. The software may be used or copied only under the terms of the license agreement. No part of this manual may be photocopied or repro- duced in any form The Math Works, Inc. FEDERAL ACQUISITI
Discount model is in terms of conditional moments The first order condition is,u'( BE, [u'(c )x 1] The expectation is conditional expectation on investor's time t information; The basic pricing equation is P, =E, (m +1X1+)