varianceTest             package:fBasics             R Documentation

_T_w_o _S_a_m_p_l_e _V_a_r_i_a_n_c_e _T_e_s_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Tests if two series differ in their distributional variance
     parameter.

_U_s_a_g_e:

      
     varianceTest(x, y, method = c("varf", "bartlett", "fligner"), 
         title = NULL, description = NULL)

_A_r_g_u_m_e_n_t_s:

    x, y: numeric vectors of data values. 

  method: a character string naming which test should be applied. 

   title: an optional title string, if not specified the inputs data 
          name is deparsed. 

description: optional description string, or a vector of character
          strings. 

_D_e_t_a_i_l_s:

     The 'method="varf"' can be used to compare variances of two 
     normal samples performing an F test. The null hypothesis is that 
     the ratio of the variances of the populations from which they were
      drawn is equal to one. 

     The 'method="bartlett"' performs the Bartlett test of the  null
     hypothesis that the variances in each of the samples are the 
     same. This fact of equal variances across samples is also called 
     _homogeneity of variances_. Note, that Bartlett's test is 
     sensitive to departures from normality. That is, if the samples 
     come from non-normal distributions, then Bartlett's test may
     simply  be testing for non-normality. The Levene test (not yet
     implemented) is an alternative to the Bartlett test that is less
     sensitive to  departures from normality. 

     The 'method="fligner"' performs the Fligner-Killeen test of  the
     null that the variances in each of the two samples are the same.

_V_a_l_u_e:

     In contrast to R's output report from S3 objects of class
     '"htest"' a different output report is produced. The classical
     tests presented here return an S4 object of class '"fHTEST"'. The
     object contains the following slots:

   @call: the function call.   

   @data: the data as specified by the input argument(s). 

   @test: a list whose elements contail the results from the
          statistical test. The information provided is similar to a
          list object of class '"htest"'. 

  @title: a character string with the name of the test. This can be 
          overwritten specifying a user defined input argument. 

@description: a character string with an optional user defined
          description.  By default just the current date when the test
          was applied will be returned. 

statistic: the value(s) of the test statistic. 

 p.value: the p-value(s) of the test. 

parameters: a numeric value or vector of parameters. 

estimate: a numeric value or vector of sample estimates. 

conf.int: a numeric two row vector or matrix of 95 

  method: a character string indicating what type of test was
          performed. 

data.name: a character string giving the name(s) of the data. 

_N_o_t_e:

     Some of the test implementations are selected from R's 'ctest' 
     package.

_A_u_t_h_o_r(_s):

     R-core team for hypothesis tests implemented from R's  package
     'ctest'.

_R_e_f_e_r_e_n_c_e_s:

     Conover, W. J. (1971); _Practical nonparametric statistics_, New
     York: John Wiley & Sons.

     Lehmann E.L. (1986);  _Testing Statistical Hypotheses_,  John
     Wiley and Sons, New York.

_E_x_a_m_p_l_e_s:

     ## rnorm - 
        # Generate Series:
        x = rnorm(50)
        y = rnorm(50)
        
     ## varianceTest -
        varianceTest(x, y, "varf")
        varianceTest(x, y, "bartlett")
        varianceTest(x, y, "fligner")

