MATLAB

: 162 b(=0.8)a (=1)c(=0.75) a-b b-c 136 214 195 219 224 197 213 187 187 230 172 227 157 114 156

= 162

n G(n) n G(n) a-b b-c

r

a-b ~ b-c ~

MATLAB ()

MATLAB ()y=normpdf(1.5,1,2) x=1.5 (=1, =2) y=fcdf(1,10, 50) Fx= 1 (n1=10, n2=50)y =tinv(0.9,10) =0.9t (, n=10)

MATLAB p(x)baotongdata.mbaotong1.m

1: = kg/m : 01

yx1x2x3 0, 1, 2, 3 ,

MATLAB () b=regress(y,X) [b,bint,r,rint,s]=regress(y,X,alpha): y~(), X~1Alpha~0.05s: 3R2F, F(1,n-2)Fpp

(210)xueya01.m

2 ~ ~ 1=0=~ 1=2=3=

y~ x1 ~x2 = 1~ x2 = 0~ 1=2=3= a0, a1, , a4

R2,F, p 1546 6883 2994 148 a4!xinjindata.m xinjin.m

3 6 x2x3, x4

x2x3, x4R2,F (33)

R2 0.957 0.999 0.9998F 226 554 36701 xinjindata2.m xinjin1.m

6(0x3=1, x4=0 x3=0, x4=1 x3=0, x4=0 x1= 0 x2 = 1~ x2 = 0~

3 yx1x2, 10 yx1x2; 160170.

x1 ()120140190130155175125145180150x2 ()10011090150210150250270300250y ()10210012077469326696585

(x1,y),(x2,y)10yx2yx1y=f(x1,x2)3

[b,bint,r,rint,stats]=regress(Y,X,alpha)3 =0.05 =0.01 R2 1

MATLAB ()rstool (x,y, 'model',alpha)x~nm, n, y~nalpha~model~4: (m=2)

3 x1=[]; x2=[]; x=[x1' x2']; y=[]';rstool(x,y, 'quadratic')Export~beta--rmse--sresiduals--()Shangpin.m

rmse 4Model: linear purequadratic interaction quadratic rmse: 18.7362 16.6436 19.1626 18.6064 =-312.5871 7.2701 -1.7337 -0.0228 0.00373

MATLAB () stepwise (x,y,inmodel,penter,premove) x~nk n, k; y~n; Inmodel~x; penter~0.05; premove~0.10

3 x=[x1;x2;x1.*x2;x1.^2;x2.^2]';stepwise(x,y')Shangpin.m

MATLAB ()x~y~ model~my =f(b,x), b b0~ b~R~J~Jacobi