最近学到gaussian distribution。但是真心不太会。手头上有个小练习可是code怎么写都不对。

To simulate random variables which are related to the measure-

ments of brain weight in weights.txt (which you will have noted are non-negative).

First, write R code that will draw samples from a Gaussian distribution with a

mean that is matched to the sample mean of the brain weights in weights.txt, and

whose standard deviation is 100. Next, write R code that implements a rejection

sampler that will draw from a truncated version of this same Gaussian distribution,

but which is constrained to non-negative quantities. Report on the eciency of your

sampler and indicate how you might improve it.

1 3.385 44.500

2 0.480 15.500

3 1.350 8.100

4 465.000 423.000

5 36.330 119.500

6 27.660 115.000

7 14.830 98.200

8 1.040 5.500

9 4.190 58.000

10 0.425 6.400

11 0.101 4.000

12 0.920 5.700

13 1.000 6.600

14 0.005 0.140

15 0.060 1.000

16 3.500 10.800

17 2.000 12.300

18 1.700 6.300

19 2547.000 4603.000

20 0.023 0.300

21 187.100 419.000

22 521.000 655.000

23 0.785 3.500

24 10.000 115.000

25 3.300 25.600

26 0.200 5.000

27 1.410 17.500

28 529.000 680.000

29 207.000 406.000

30 85.000 325.000

31 0.750 12.300

32 62.000 1320.000

33 6654.000 5712.000

34 3.500 3.900

35 6.800 179.000

36 35.000 56.000

37 4.050 17.000

38 0.120 1.000

39 0.023 0.400

40 0.010 0.250

41 1.400 12.500

42 250.000 490.000

43 2.500 12.100

44 55.500 175.000

45 100.000 157.000

46 52.160 440.000

47 10.550 179.500

48 0.550 2.400

49 60.000 81.000

50 3.600 21.000

51 4.288 39.200

52 0.280 1.900

53 0.075 1.200

54 0.122 3.000

55 0.048 0.330

56 192.000 180.000

57 3.000 25.000

58 160.000 169.000

59 0.900 2.600

60 1.620 11.400

61 0.104 2.500

62 4.235 50.400

数据都在这里。。求教code。。首先是作出和weights有关的gaussian distribution。之后再rejection sampling。