[R] scatter.smooth() fitted by loess

[phoebe kong]

Hi there,

I would like to draw a scatter plot and fit a smooth line by loess.
Below is the data.
However, the curve line started from 0, which my "resid" list doesn't
consist of 0 value.
It returned some warnings which I don't know if this is the reason
affecting such problem. Here I also attached the warning messages.
Please let me know if there is a solution to fix this. Thank you very
much!

YMRS_Sum<-c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 2, 2, 0, 0, 0, 1, 1,
4, 0, 0, 2, 0, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 1, 4, 2, 1, 2, 0, 1,
0, 0, 0, 0, 2, 0, 0, 3, 0, 0, 0, 0, 2, 0, 4, 0, 2, 0, 0)

resid<-c(80.1150, 84.0279, 88.3736, 90.1557, 55.1979, 78.4293,
87.4367, 74.0271, 80.8871, 91.5685, 82.4154, 73.3080, 66.7786,
70.2486, 82.4971, 77.3792, 70.7731, 66.9593, 85.5515 81.4071, 68.6646,
89.8271, 91.6041, 85.1980, 80.6071, 86.4362, 86.2915, 86.4493,
87.8664, 84.5150, 64.4975, 79.1246, 84.9350, 89.1608, 92.7546,
70.0253, 81.4146, 73.2755, 82.5200, 79.7164, 92.0786, 82.5633,
84.4336, 84.0193, 64.8029, 87.4864, 86.3338, 75.6758, 86.8567,
85.1077, 88.9533, 81.7240, 84.1713, 80.0400, 77.6050, 81.4436,
83.8379, 72.5050, 80.5423, 83.2564, 84.1436, 90.0662, 84.5293,
81.6771, 90.6425, 90.3285, 76.2371, 87.3625, 70.7917, 77.0993,
88.3608, 89.7200, 79.1031, 79.7421, 84.2469, 83.9371, 73.8800,
89.3921, 89.3900, 86.8921, 85.7036, 85.2664, 83.8700, 90.5493)

> scatter.smooth(YMRS_Sum,resid)

Warning messages:
1: at  -0.02
2: radius  0.0004
3: all data on boundary of neighborhood. make span bigger
4: pseudoinverse used at -0.02
5: neighborhood radius 0.02
6: reciprocal condition number  nan
7: zero-width neighborhood. make span bigger
8: There are other near singularities as well. 1
9: at  -0.02
10: radius  0.0004
11: all data on boundary of neighborhood. make span bigger
12: pseudoinverse used at -0.02
13: neighborhood radius 0.02
14: reciprocal condition number  nan
15: zero-width neighborhood. make span bigger
16: There are other near singularities as well. 1
17: at  -0.02
18: radius  0.0004
19: all data on boundary of neighborhood. make span bigger
20: pseudoinverse used at -0.02
21: neighborhood radius 0.02
22: reciprocal condition number  nan
23: zero-width neighborhood. make span bigger
24: There are other near singularities as well. 1
25: at  -0.02
26: radius  0.0004
27: all data on boundary of neighborhood. make span bigger
28: pseudoinverse used at -0.02
29: neighborhood radius 0.02
30: reciprocal condition number  nan
31: zero-width neighborhood. make span bigger
32: There are other near singularities as well. 1
33: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  at  -0.02
34: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  radius  0.0004
35: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  all data on boundary of neighborhood. make span bigger
36: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  pseudoinverse used at -0.02
37: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  neighborhood radius 0.02
38: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  reciprocal condition number  nan
39: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  zero-width neighborhood. make span bigger
40: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize =
FALSE,  ... :
  There are other near singularities as well. 1


Thanks,
Phoebe