Lilliefors test for goodness of fit

This function performs the Lilliefors test

lilliefors.test(sequence, distribution = "NORMAL")

Arguments

sequence	Secuence of data
distribution	Distribution name to perform test

Value

A list with pvalues for alternative hypothesis, statistics, method and data name

Examples

lilliefors.test(rnorm(100))
#> $data.name
#>  [1] "c(-2.59127668649719, -2.14171496989577, -2.13648505875235, -1.95939274298821, "  
#>  [2] "-1.94442979606088, -1.9258996843082, -1.49110768757591, -1.29293344281375, "     
#>  [3] "-1.21563461507481, -1.21048443547795, -1.17590865860338, -1.165502702372, "      
#>  [4] "-1.12276560437158, -1.10345497881862, -1.09001489316387, -1.08992687011203, "    
#>  [5] "-1.03299852224827, -1.01455496099666, -0.995182598372791, -0.985060603401776, "  
#>  [6] "-0.976161735168897, -0.959891303459105, -0.912223369111775, -0.904379810420577, "
#>  [7] "-0.897136227564941, -0.804305141797847, -0.778002995779615, -0.768450416671552, "
#>  [8] "-0.692382057232101, -0.644412824563362, -0.638809138156435, -0.570365386719422, "
#>  [9] "-0.558175308831016, -0.54531250236706, -0.461894875570348, -0.443467296163856, " 
#> [10] "-0.36392249467283, -0.354737542671058, -0.349130227626214, -0.21057554287628, "  
#> [11] "-0.173610772927079, -0.163619535122618, -0.148609930024847, -0.137891293320244, "
#> [12] "-0.104109587808189, -0.0996495969624928, -0.0955250021814966, "                  
#> [13] "-0.0368578043965597, -0.0133446224188618, 0.0129256170760981, "                  
#> [14] "0.0212030187691375, 0.0374858781520228, 0.0589607135770673, 0.073005135879982, " 
#> [15] "0.0760285839436088, 0.0840195746793427, 0.084279106674348, 0.113452977009962, "  
#> [16] "0.141221440231729, 0.211699057272924, 0.231269775585736, 0.249637811218961, "    
#> [17] "0.272639705982461, 0.305703121474774, 0.343268902869148, 0.350454675193676, "    
#> [18] "0.355107478106701, 0.355411049488421, 0.370369327672636, 0.378058608040172, "    
#> [19] "0.382307501605425, 0.431336940092344, 0.502443315354218, 0.506351570813164, "    
#> [20] "0.526454646462741, 0.527791603574717, 0.585713525647744, 0.645026207142606, "    
#> [21] "0.683137531039301, 0.757792666481458, 0.804841249833058, 0.811999621157851, "    
#> [22] "0.869509264973104, 0.983191348209893, 1.07298983556177, 1.07348373162136, "      
#> [23] "1.10813182174417, 1.13935565815181, 1.18707789900182, 1.20423237108792, "        
#> [24] "1.26049311537608, 1.27687396824355, 1.60151723918031, 1.63454727421707, "        
#> [25] "1.65605572109179, 1.70379903970893, 1.71159542439079, 1.76400333319773, "        
#> [26] "2.16438932808248, 2.16882571617544)"                                             
#> 
#> $parameters
#>        mean          sd 
#> -0.05620214  1.00179073 
#> 
#> $statistic
#>         Dn 
#> 0.05335127 
#> 
#> $p.value
#> Asymptotic p-value <=  
#>                      1 
#> 
#> $method
#> [1] "Lilliefors"
#> 
lilliefors.test(rexp(100, rate=5), distribution = "EXPONENTIAL")
#> $data.name
#>  [1] "c(0.0010790903121233, 0.00597165785729885, 0.0122005446082925, "                 
#>  [2] "0.0126622689887881, 0.0183763982728124, 0.0207933576777577, 0.0220732323380558, "
#>  [3] "0.0232897393043151, 0.0244492394112001, 0.02571064196527, 0.0288801482878625, "  
#>  [4] "0.0304510441716404, 0.0314859329929919, 0.0335726437158883, 0.0337172019894414, "
#>  [5] "0.036382397916168, 0.0367415848083279, 0.0395590633128967, 0.0399612907320261, " 
#>  [6] "0.0418477232348953, 0.0476440755650401, 0.0521262491121888, 0.0564054161310196, "
#>  [7] "0.0663925656117499, 0.066978728864342, 0.0678529316559434, 0.0729585279710591, " 
#>  [8] "0.078149361482653, 0.083899955265224, 0.0849323369276305, 0.0861044004559517, "  
#>  [9] "0.0893603842351825, 0.0945796450600028, 0.101457429863513, 0.102188837528229, "  
#> [10] "0.105854580644518, 0.107192153390497, 0.109463570825756, 0.110173601191491, "    
#> [11] "0.112276318389922, 0.113998559303582, 0.114078452438116, 0.114651502203196, "    
#> [12] "0.121045817341655, 0.123140147980303, 0.126765386946499, 0.129168799612671, "    
#> [13] "0.130569519847631, 0.13416891656816, 0.14425463366362, 0.146144947214963, "      
#> [14] "0.151149924079318, 0.153261350098159, 0.156963343723657, 0.159335933768728, "    
#> [15] "0.166316062139811, 0.173267083497925, 0.173327478012981, 0.179127344294431, "    
#> [16] "0.183336287002244, 0.183974362970471, 0.194651710047367, 0.204826918794754, "    
#> [17] "0.205359864226523, 0.21035791299397, 0.211008431381526, 0.217548364951255, "     
#> [18] "0.227268382153454, 0.233421102344039, 0.238326229705455, 0.250683948389235, "    
#> [19] "0.262684155247154, 0.268139188542011, 0.269632941476049, 0.273019912085476, "    
#> [20] "0.274296591608765, 0.275141469008269, 0.281955415738707, 0.292146776369999, "    
#> [21] "0.293953770442323, 0.299276759831195, 0.318325978198879, 0.321982626600151, "    
#> [22] "0.338722895069008, 0.356764109182335, 0.357627921534662, 0.37021120971251, "     
#> [23] "0.390918471274858, 0.395575476793532, 0.399948894588237, 0.402689949033742, "    
#> [24] "0.423280375053115, 0.448636255015559, 0.472872885663934, 0.482820648513418, "    
#> [25] "0.486632133949413, 0.546229722698159, 0.561922232773075, 0.565701997246513, "    
#> [26] "0.697597628521494)"                                                              
#> 
#> $parameters
#>     mean 
#> 0.186154 
#> 
#> $statistic
#>         Dn 
#> 0.09016906 
#> 
#> $p.value
#> Asymptotic p-value <=  
#>                      1 
#> 
#> $method
#> [1] "Lilliefors"
#>