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1、第二章作业刘洪骏20082012162.11首先在R选单小选择改变工作目录，改为存放数据的文件夹，这样就可以读取数据了。(1)经验累积分布、直方图、Q-Q图>a=read.table("beenswax.txt”,header二T)>mode(a)[1]"list">names(a)[1]"MeltingPoint""Hydrocarbon">dim(a)[1]592>attach(a)>M=MeltingPoint>M[1]63.7863.4563.5863.0863.4064.4263.2763.1063.3463.5063.8363.63[13]63.2763.3063.8363.
2、5063.3663.8663.3463.9263.8863.3663.3663.51[25]63.5163.8464.2763.5063.5663.3963.7863.9263.9263.5663.4364.21[37]64.2464.1263.9263.5363.5063.3063.8663.9363.4364.4063.6163.03[49]63.6863.1363.4163.6063.1363.6963.0562.8563.3163.6663.60>ecdf(M)EmpiricalCDFCall:ecdf(M)x[l:40]=62.85,63.03,63.05,64.4,64.42
3、>plot(ecdf(M))ecdf(M)x>H=Hydrocarbon>H[1]14.2714.8012.2817.0915.1012.9215.5615.3815.1513.9814.9015.91[13]14.5215.6313.8313.6613.9814.4714.6514.7315.1814.4914.5615.03[25]15.4014.6813.3314.4114.1915.2114.7514.4114.0413.6815.3114.32[37]13.6414.7714.3014.6214.1015.4713.7313.6515.0214.0114.9215.47[49]
4、13.7514.8715.2814.4313.9614.5715.4915.1314.2314.4414.57>ecdf(H)EmpiricalCDFCall:ecdf(H)x[l:55]=12.28,12.92,13.33,15.91,17.09>plot(ecdf(H))ecdf(H)121314151617x>hist(M)HistogramofMHistogramofH>qqplot(M,H)M(1)找出分位数>?quantile>quantile(M/probs=seq(0,l,0.05))40%45%100%40%45%100%0%5%10%15%20%25%30%35%50
5、%62.85063.07763.13063.29163.32863.36063.39463.43063.50063.50163.53055%60%65%70%75%80%85%90%95%63.57863.60863.67463.78063.83563.86863.92063.96864.24364.420>quantile(H,probs=seq(0,1,0.05))0%5%10%15%20%25%30%35%50%12.28013.60913.67613.80613.98014.07014.24614.34714.43214.49314.57055%60%65%70%75%80%85
6、%90%95%14.64714.74614.84914.98015.11515.19215.33115.47015.56717.090(2)由QQ图可以看出近似服从高斯分布。2.12先将数据记录在excel中,在转换成txt,以便R读取。文件名为"2.12〃>b=read.table("2.12.txt"/header=T)>bNonPIPaAmMoPeTr117426310514119910814122242131031681433411843260231145781131591254255291103164225135227516516814412717623919462371219
7、41141441361557191137359687140121810010213322212013412911158983165100185792189433237168173188317>survival=function(x){length(x)->nx.sort=sort(x)x.rank=rank(x.sort)x.cdf=x.rank/nretum(rbind(x.sort,(l-x.cdf)))}>bl=list()(
