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ÓÃmatlabÄâºÏÈýÔªÏßÐԻع鷽³Ì£¬ÎÒ×Ô¼ºÅªÁËÒ»¸öÈçÏ x1=[23.00 23.00 23.00 23.00 23.00 28.00 28.00 28.00 28.00 28.00]'; x2=[0.30 0.30 0.30 0.30 0.30 0.10 0.10 0.10 0.10 0.10]'; x3=[0.00 0.69 1.09 1.38 1.61 0.00 0.69 1.09 1.38 1.61]'; y=[-0.91 -0.35 -0.05 0.15 0.29 -0.58 -0.04 0.23 0.41 0.54]; x=[ones(10,1) x1 x2 x3]; >> [b,bint,r,rint,stats]=regress(y,x); ??? Error using ==> or Matrix dimensions must agree. Error in ==> regress at 70 wasnan = (isnan(y) | any(isnan(X),2)); >> b,bint,stats,rcoplot(r,rint) b = 0 -0.0115 -1.7878 0.6751 bint = 0 0 -0.0168 -0.0062 -2.2782 -1.2973 0.5701 0.7800 stats = 0.9747 134.6812 0.0000 0.0059 ÎÊÌ⣺ 1.ÎÒ±àдµÄ³ÌÐò¶ÔÂ𣿠2.ÊäÈë³ÌÐòÖУ¬×ÜÊÇ»á³öÏÖwarningµÄÄǶÎÎÄ×Ö£¬²»ÖªµÀÔõôÐ޸ģ¿ |
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2Â¥2012-07-11 09:50:45
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ÇëÎÊyд³ÉÁÐÏòÁ¿ºóÓÖ³öÏÖÎÊÌâÁË£¬ÕâÊÇÔõô»ØÊ°¡£¿£¿ >> x1=[23.00 23.00 23.00 23.00 23.00 28.00 28.00 28.00 28.00 28.00]'; x2=[0.30 0.30 0.30 0.30 0.30 0.10 0.10 0.10 0.10 0.10]'; x3=[0.00 0.69 1.09 1.38 1.61 0.00 0.69 1.09 1.38 1.61]'; >> y=[-0.91 -0.35 -0.05 0.15 0.29 -0.58 -0.04 0.23 0.41 0.54]; >> x=[ones(10,1) x1 x2 x3]; >> [b,bint,r,rint,stats]=regress(y,x); Warning: X is rank deficient to within machine precision. > In regress at 82 >> b,bint,stats,rcoplot(r,rint) |
3Â¥2012-07-11 10:17:45
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Most likely you have too many predictor variables, and too few observations. As an alaogy, imagine trying to fit a cubic polynomial regression with only two observations. REGRESS will make a choise about which coefficients to set to zero, but it can't possibly know what you really want. ±äÁ¿Ì«¶à£¬Äã¿ÉÒÔÊÔһϣ¬·Ö±ðʹÓÃx(:,1:2), x(:,1:3), x(:,2:3)Ëãһϣ¬Ê¹ÓÃ3ÁÐʱ×Ü»á³öÏÖÒ»¸öb=0¡£ |

4Â¥2012-07-11 10:38:00
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5Â¥2012-07-11 11:29:51
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¹ÅµÀÎ÷·ç11: ½ð±Ò+10, ¡ï¡ï¡ïºÜÓаïÖú, ½â¾öÁËÎÊÌâ 2012-07-11 12:33:22
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6Â¥2012-07-11 11:51:47
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7Â¥2012-07-11 12:33:46
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8Â¥2012-09-28 20:31:01
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9Â¥2013-05-14 13:15:22
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µü´úÊý: 33 ¼ÆËãÓÃʱ(ʱ:·Ö:Ãë:΢Ãë): 00:00:00:241 ÓÅ»¯Ëã·¨: Âó¿äÌØ·¨(Levenberg-Marquardt) + ͨÓÃÈ«¾ÖÓÅ»¯·¨ ¼ÆËã½áÊøÔÒò: ´ïµ½ÊÕÁ²Åжϱê×¼ ¾ù·½²î(RMSE): 0.0274286872091944 ²Ð²îƽ·½ºÍ(SSE): 0.00752332882019822 Ïà¹ØÏµÊý(R): 0.998018933040592 Ïà¹ØÏµÊý֮ƽ·½(R^2): 0.996041790707481 ¾ö¶¨ÏµÊý(DC): 0.996041790707481 ¿¨·½ÏµÊý(Chi-Square): -0.0155244265746169 Fͳ¼Æ(F-Statistic): 2013.11596653563 ²ÎÊý ×î¼Ñ¹ÀËã ---------- ------------- a -37.3038021226221 b -934.025053065556 c 0.724150995543315 d 1137.33012469023 ====== ½á¹ûÊä³ö ===== No ʵ²âÖµy ¼ÆËãÖµy 1 -0.91 -0.8648400 2 -0.35 -0.3651759 3 -0.05 -0.0755155 4 0.15 0.1344883 5 0.29 0.3010431 6 -0.58 -0.5788400 7 -0.04 -0.0791759 8 0.23 0.2104845 9 0.41 0.4204883 10 0.54 0.5870431 |
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