[R] kernel smoothing of disease rates at locations

[Oarabile Molaodi]

I want to do kernel smoothing on the standardised mortality rates at 
specified location(x-y coordinates) and be able to produce contour map. 
I've tried to use the package called fields in R (function smooth.2d) 
but the problem is I get negative results after smoothing and I do not 
understand why? Your contributions will be highly appreciated or if 
there is any package that can do this I will be happy to know about it.  
Thanks in advance for your comments.
Oarabile

Below is how my data in R looks like
  Xcoord    Ycoord       smr
1  383894.70  653202.8 1.5816327
2  339053.00  631770.9 1.0003473
3  369164.50  609973.2 1.2943872
4  313477.70  640382.8 0.9443508
5  290748.80  695088.8 1.1662125
6  287547.50  679829.6 0.9433962
7  259031.90  704478.3 1.0184905
8  329107.60  585753.3 1.0445860
9  292170.20  578978.2 1.1287758
10 268330.90  564281.7 0.9805996
11 227395.50  561524.6 1.1947431
12 310130.70  689395.0 1.0991957
13 325756.00  696565.6 1.1734694
14 339427.20  713217.2 0.8724100
15 391752.10  805661.5 1.2483221
16 385935.90  851044.5 1.0558140
17 372471.20  826373.7 1.4220183
18 354901.70  791107.2 0.9175084
19 324944.10  842040.8 1.0447080
20 275672.50  802570.4 0.9899329
21 320750.00  954769.7 1.0866834
22 243489.20  832748.8 1.0995658
23 166559.70  786365.3 1.0401267
24 288160.80  846054.4 1.0299003
25 220347.00  869181.0 0.9529435
26 175863.63  822593.9 0.9902252
27 246114.40  938419.3 0.8909370
28 359070.60  669738.3 0.9883721
29 320614.70  670434.2 1.1288534
30 331414.80  659972.3 0.9070866
31 299336.90  666122.9 0.7969349
32 156965.25  708047.7 1.1410460
33 253867.30  674916.5 0.9256710
34 249188.40  674272.8 1.0869565
35 272463.00  679495.3 0.8576698
36 252643.80  611378.4 0.8615611
37 212637.35  643725.0 0.8596604
38 234751.95  691803.4 0.9706546
39 264856.20  644684.8 0.8468395
40 253949.30  653042.5 0.8106169
41 260412.35  663552.2 0.9253686
42 270807.60  657454.0 0.9002826
43 228477.30  670443.2 1.0782502
44 248215.30  641897.3 0.9240407
45 229797.50  596059.0 1.1579197
46 291725.00  635771.8 0.8908766
47 278012.80  667982.0 1.0240000
48 279490.80  659761.6 0.9828301
49 242791.70  662651.8 1.0230584
50 263217.20  675295.2 0.9759817
51 341138.80  754471.3 0.9505541
52 334963.00  735075.4 0.9264498
53 286139.70  733611.6 0.9052453
54 354015.60 1025696.8 0.8905506
55 455775.60 1201636.0 1.0862620
56  88429.32  854994.4 0.9577015