Wen-Feng-
The term LINEAR is a difficult term.
As I mentioned to you in an earlier message (included for
reference as the end of this message),
a LINEAR STATISTICAL MODEL is "LINEAR" in the unknown
coefficients, a1, a2,... ap in the model:
Y = a1*X1 + a2*X2 + ... + ap*Xp + E
The X predictors can be ANY NUMBERS THAT WE LIKE.
If we write --
Y = a1*U + a2*X + a2*X^2 + E
where
U = 1
X = a continuous predictor
X^2 = X*X
E = error or residual
we might say that the function is NON-LINEAR in the two-dimensional, Y-X plane,
but it is LINEAR in the three dimensional space of Y-X-X^2. With 3-D displays that we
can rotate as we would like, it is enlightening to observe that the CURVE seen in the
two-dimensional
space lies in a PLANE in the three-dimensional space of Y-X-X^2.
-- Joe
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* San Antonio, TX 78228-2402 San Antonio, TX 78229 *
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----- Original Message -----
From: Wen-Feng Hsiao <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Saturday, April 15, 2000 5:14 AM
Subject: Re: linear model or interactive model?
| Dear Hartig,
|
| Thanks for your reply. I am sorry for my poor knowledge in statistics.
| But I wonder why the definition of 'linearity' of statistics is different
| from that of engineering mathematics, which defines 'linear' as:
|
| Each unknown xj appears to the first power only, and that there are no
| cross product terms xi*xj with i!=j.
|
| Wen-Feng
|
| In article <[EMAIL PROTECTED]>,
| [EMAIL PROTECTED] says...
| > Generally, you can include an interaction (or moderator) term in a linear
| > model, like
| > y = b0 + b1 * x1 + b2 * x2 + b3 * x1*x2,
| > and the model still is linear. If you decide not to include x1 and x2, like
| > y = b0 + b1 * x1*x2,
| > you still have a linear model.
|
============================
----- Original Message -----
From: Joe Ward <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>; Wen-Feng Hsiao <[EMAIL PROTECTED]>
Sent: Thursday, April 13, 2000 10:30 AM
Subject: Re: linear model or interactive model?
----- Original Message -----
From: Wen-Feng Hsiao <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Thursday, April 13, 2000 3:06 AM
Subject: linear model or interactive model?
| Dear all,
|
| Suppose I have an aggregation model which is in the following form:
| Y = c1*(X11 * X12) + c2*(X21 * X22)?
|
| This model could be thought as an aggregation of two knowledge, namely
| X1. and X2.. Each knowledge contains two pieces of information
| (attributes). For example, X1 contains X11 ans X12. Now if X.1 is the
| height, and X.2 is the weight of a person. Then, the aggregation of any
| two persons, say, Student1(height=170cm, weight=60kg),
| Student2(height=180cm, weight=68kg) can be represented by
|
| Y = 170*60+180*68=22440.
|
| My question: a model as the above form is linear or interactive? I doubt
| it is not a linear model. Since it is not in this form: Y= c1 X1 + c2 X2,
| where c1 and c2 are constant. I doubt it is not a pure interactive form,
| since X.1 and X.2 are dependent. Sorry for this stupid question.
|
| Wen-Feng
|
==== Joe Ward writes|
===========================================================================
Wen-Feng---
Your model --
Y = X11 * X12 + X21 * X22.
does not have any unknowns.
Did you mean to write:
Y = c1*(X11 * X12) + c2*(X21 * X22)?
All models of the form:
Y = c1*X1 + c2*X2 + ... + cp*Xp + E
are LINEAR MODELS.
It does not matter what NUMBERS are included in the Xs.
Y = c1*X1 + c2*X2 + c3*(X1*X2) + c4*(X1^2) + c5*(lnX1) + E
is LINEAR in the unknown coefficients c1, c2, ...
The most useful Xs are the BINARY( 1 or 0) predictors.
--- Joe
************************************************************************
* Joe Ward Health Careers High School *
* 167 East Arrowhead Dr 4646 Hamilton Wolfe *
* San Antonio, TX 78228-2402 San Antonio, TX 78229 *
* Phone: 210-433-6575 Phone: 210-617-5400 *
* Fax: 210-433-2828 Fax: 210-617-5423 *
* [EMAIL PROTECTED] *
* http://www.ijoa.org/joeward/wardindex.html *
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