r软件中的主成分分析

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1、问题表1为某地区农业生态经济系统各区域单元和关指标数据，运用主成分分析方法，用更少的指标信息较为精确地描述该地区农业生态经济的发展状况。表1某农业生态经济系统各区域单元的有关数据1模型选择Xu人口密度（人/km2）x3：森林覆盖率（％）x5：人均粮食产量（kg/人）x7：耕地占土地面积比率（％）x9：灌溉田占耕地面积之比（°%）X2：人均耕地面积（ha）x4：农民人均纯收入（元/人）X6：经济作物占农作物播面比例（％）x8：果园与林地面积之比（％）样本序号Xi:人U密度（人/km2）x2：人均耕地而积（ha）x3：森林覆盖率（％）x4:农民人均纯收入（元/人＞x5：人均粮

2、食产量（kg/人｝x6：经济作物占农作物播而比例（%）x7:耕地占土地面积比率（％）x8:果园与林地面积之比（％）x9：灌溉田A耕地面积之比（％）1363.9120.35216.101192.11295.3426.72418.4922.23126.2622141.5031.68424.3011752.35452.2632.31414.4641.45527.0663100.6951.06765.6011181.54270.1218.2660.1627.47412.4894143.7391.33633.2051436,12354.2617.48611.8051.89217.5

3、345131.4121.62316.6071405.09586.5940.68314.401030322.932668.3372.03276.2041540.29216.398.1284.0650.0114.861795.4160.80171.106926.35291.528.1354.0630.0124.862862.9011.65273.3071501.24225.2518.3522.6450.0343.201986.6240.84168.904897.36196.3716.8615.1760.0556.1671091.3940.81266.502911.24226.

4、5118.2795.6430.0764.4771176.9120.85850.302103.52217.0919.7934.8810.0016.1651251.2741.04164.609968.33181.384.0054.0660.0155.4021368.8310.83662.804957.14194.049.1104.4840.0025.7901477.3010.62360.102824.37188.0919.4095.7215.0558.4131576.9481.02268.0011255.42211.5511.1023.1330.0103.4251699.26

5、50.65460.7021251.03220.914.3834.6150.0115.59317118.5050.66163.3041246.47242.1610.7066.0530.1548.70118141.4730.73754.206814.21193.4611.4196.4420.01212.94519137.7610.59855.9011124.05228.449.5217.8810.06912.65420117.6121.24554.503805.67175.2318.1065.7890.0488.46121122.781解答：0.73149.1021313.1

6、1236.2926.7247.1620.09210.078做主成分分析，命名第一主成分为Z1,第二主成分为Z2,第三主成分为Z3,依次类推，当前m个主成分的累积贡献率达到80%及以上，我们就说脑的大小与前m主成分有关。并求解转化后的冗^与Xj之间的相关系数。2问题解答在F盘保存某地区农业生态经济系统各区域单元相关指标数data.txt（见附录）。在R软件中输入代码：I>rnydata<-read,table(rrF:/data.txtrF)>mydata.pr<—princomp(mydata,cor=TRUE)>summary(mydata.pr,loadings=TR

7、UE)得到如下结果：Importanceofcomponents:Corop.1Comp.2Comp.3Comp.4Comp.5Comp.6Comp.7Comp.8Comp.9Standarddeviation2.1589621.44550761.02127080.712335880.56140010.438877880.338214970.2129002300.177406876ProportionofVariance0.5179020.23216580.11588820.056380270.03501890.0214015