上海本地网站建设,微信网站怎么建设,网页设计教程入门,进出长春最新规定先PS一个#xff1a;考虑到这次的题目本身的特点 尝试下把说明性内容都直接作为备注写在语句中 另外用于说明的部分例子参考了我的教授Guy Yollin在Financial Data Analysis and Modeling with R这门课课件上的例子 部分参考了相关package的帮助文档中的例子 下面正题- 戌 考虑到这次的题目本身的特点 尝试下把说明性内容都直接作为备注写在语句中 另外用于说明的部分例子参考了我的教授Guy Yollin在Financial Data Analysis and Modeling with R这门课课件上的例子 部分参考了相关package的帮助文档中的例子 下面正题- 戌 # Assume the predetermined significance level is 0.05.假设预定的显着性水平是0.05。 # 1 Shapiro-Wilk Test # Null hypothesis:零假设: # The sample came from a normally distributed population.样本来自正态分布总体 install.packages(stats) library(stats) # args() function displays the argument names and corresponding default values of a function or primitive.args()函数显示一个函数的参数名称和相应的默认值。 args(shapiro.test)function (x) NULL # Example 1: # Test random sample from a normal distribution.测试来自正态分布的随机抽样。 set.seed(1) x - rnorm(150) res - shapiro.test(x) res$p.value # 0.05[1] 0.7885523 # Conclusion: We are unable to reject the null hypothesis.结论我们无法拒绝零假设。 # Example 2: # Test daily observations of SP 500 from 1981-01 to 1991-04.测试SP500指数从1981-01到1991-04的日观察值。 install.packages(Ecdat) library(Ecdat) data(SP500) class(SP500)[1] data.frame SPreturn SP500$r500 # use the $ to index a column of the data.frame用$符号取出数据框中的一列 (res - shapiro.test(SPreturn)) Shapiro-Wilk normality testdata: SPreturnW 0.8413, p-value 2.2e-16 names(res)[1] statistic p.value method data.name res$p.value # 0.05[1] 2.156881e-46 # Conclusion: We should reject the null hypothesis.结论我们应该拒绝零假设。 # 2 Jarque-Bera Test # Null hypothesis: # The skewness and the excess kurtosis of samples are zero.样本的偏度和多余峰度均为零 install.packages(tseries) library(tseries) args(jarque.bera.test)function (x) NULL # Example 1: # Test random sample from a normal distribution set.seed(1) x - rnorm(150) res - jarque.bera.test(x) names(res)[1] statistic parameter p.value method data.name res$p.value # 0.05X-squared 0.8601533 # Conclusion: We should not reject the null hypothesis. # Example 2: # Test daily observations of SP 500 from 1981–01 to 1991–04 install.packages(Ecdat) library(Ecdat) data(SP500) class(SP500)[1] data.frame SPreturn SP500$r500 # use the $ to index a column of the data.frame (res - jarque.bera.test(SPreturn)) Jarque Bera Testdata: SPreturnX-squared 648508.6, df 2, p-value 2.2e-16 names(res)[1] statistic parameter p.value method data.name res$p.value # 0.05X-squared 0 # Conclusion: We should reject the null hypothesis. # 3 Correlation Test # Null hypothesis: # The correlation is zero.样本相关性为0 install.packages(stats) library(stats) args(getS3method(cor.test,default))function (x, y, alternative c(two.sided, less, greater), method c(pearson, kendall, spearman), exact NULL, conf.level 0.95, continuity FALSE, ...) NULL # x, y: numeric vectors of the data to be testedx, y: 进行测试的数据的数值向量 # alternative: controls two-sided test or one-sided testalternative: 控制进行双侧检验或单侧检验 # method: pearson, kendall, or spearman # conf.level: confidence level for confidence intervalconf.level: 置信区间的置信水平 # Example: # Test the correlation between the food industry and the market portfolio.测试在食品行业的收益和市场投资组合之间的相关性。 data(Capm,packageEcdat) (res - cor.test(Capm$rfood,Capm$rmrf)) Pearsons product-moment correlation皮尔逊积矩相关data: Capm$rfood and Capm$rmrft 27.6313, df 514, p-value 2.2e-16alternative hypothesis: true correlation is not equal to 0备择假设真正的相关性不等于095 percent confidence interval:95%置信区间 0.7358626 0.8056348sample estimates:样本估计 cor 0.7730767 names(res)[1] statistic parameter p.value estimate [5] null.value alternative method data.name [9] conf.int res$p.value # 0.05[1] 0 # Conclusion: We should reject the null hypothesis.
