Biblioteca de estadistica descriptiva en R
# install.packages("devtools")
devtools::install_github("ljofre/epg3308")
Datos de prueba
>library(describeNsimulate)
>data("albahaca")
>head(albahaca)
produccion temp alt n.riegos hum sexo marca cuidado
1 46.44 14.93 590 9 2 0 3 1
2 27.77 13.05 586 5 2 0 2 1
3 47.02 18.86 939 12 1 1 1 1
4 32.38 14.32 833 8 3 1 2 2
5 30.40 13.34 819 7 1 0 1 1
6 27.24 12.95 604 4 3 1 3 1
funciones básicas de estadistica descriptiva
# Coeficiente de Asimetria de Fisher
> asimetria.fisher(albahaca$produccion,'SI')
[1] "Asimetria Negativa"
[1] -0.1934995
#Curtosis
> curtosis(albahaca$produccion,'SI')
[1] "Distribucion Platicurtica"
[1] 2.251493
#Cuartiles *******
> cuartiles(albahaca$produccion)
Cuartiles
Q1 29.26
Q2 38.97
Q3 46.45
#Correlacion de Pearson *********
> corr.pearson(albahaca,"n.riegos","produccion")
[1] 0.7930546
[1] "Asosiacion Lineal Positiva"
#Matriz Correlaciones Pearson
> corr.matrix.pearson(albahaca)
produccion temp alt n.riegos
produccion 1.0000000 0.3567275 -0.3984812 0.7930546
temp 0.3567275 1.0000000 0.1889965 0.2377609
alt -0.3984812 0.1889965 1.0000000 0.1408494
n.riegos 0.7930546 0.2377609 0.1408494 1.0000000
#Matriz Correlaciones Spearman
> corr.matrix.spearman(albahaca)
produccion temp alt n.riegos
produccion 1.0000000 0.8631957 0.8190119 0.8575672
temp 0.8631957 1.0000000 0.8468730 0.7956535
alt 0.8190119 0.8468730 1.0000000 0.7920263
n.riegos 0.8575672 0.7956535 0.7920263 1.0000000
#Covarianza
> covarianza(albahaca$produccion,albahaca$temp)
[1] 10.11587
#Coeficiente Variacion
> coeficiente.variacion(albahaca$produccion)
[1] 0.2882387
#Promedio
> promedio(albahaca$produccion)
[1] 37.5985
#Suma
> suma(albahaca$produccion)
[1] 1503.94
descriptive.categorical(albahaca)
[1] "hum"
hum n proporcion odds error std
1 1 7 0.175 0.2121 0.0601
2 2 15 0.375 0.6000 0.0765
3 3 18 0.450 0.8182 0.0787
[1] "sexo"
sexo n proporcion odds error std
1 0 19 0.475 0.9048 0.079
2 1 21 0.525 1.1053 0.079
[1] "marca"
marca n proporcion odds error std
1 1 12 0.3 0.4286 0.0725
2 2 16 0.4 0.6667 0.0775
3 3 12 0.3 0.4286 0.0725
[1] "cuidado"
cuidado n proporcion odds error std
1 1 20 0.5 1 0.0791
2 2 20 0.5 1 0.0791
> descriptive.continue(albahaca)
n promedio suma std CV asimetria curtosis minimo maximo Q1 Q2
produccion 40 37.598 1503.94 10.837 0.288 -0.193 2.251 12.94 60.31 35.67 39.31
temp 40 16.466 658.64 2.617 0.159 -0.018 1.727 12.07 20.92 18.65 18.20
alt 40 790.375 31615.00 158.639 0.201 -0.185 1.426 502.00 988.00 779.00 974.00
n.riegos 40 7.500 300.00 2.253 0.300 0.131 1.948 4.00 12.00 6.50 9.00
Q3
produccion 35.67
temp 18.65
alt 779.00
n.riegos 6.50
#Simulacion Variable Aleatoria Bernulli
> sim.bernulli(100,0.4)
[1] 0 0 0 1 0 1 0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 1 1 0 1 1 1 0 1 1 0 1 0 0 1 1 1 0
[47] 0 0 1 0 1 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0 1 0 0 1
[93] 1 0 0 1 1 1 1 0
[1] "Porcentaje de unos"
[1] 0.45
[1] "Porcentaje de ceros"
[1] 0.55
#Simulacion Variable Aleatoria Binomial
> sim.binomial(100,30,0.4)
[1] 16 16 11 13 14 11 8 13 12 12 13 12 11 11 14 11 10 11 10 9 15 14 10 18 16 18 13 9 10 13 13
[32] 12 14 11 11 13 13 13 10 10 12 16 14 10 9 18 11 11 6 16 13 11 8 7 8 8 16 14 14 11 13 16
[63] 12 11 13 9 14 13 12 15 13 11 12 11 13 11 9 14 11 6 15 7 9 9 13 12 12 11 18 12 13 11 16
[94] 18 15 15 9 10 13 11
#Simulacion Variable Aleatoria Exponencial
> sim.exponencial(100,7)
[1] "Datos generados"
[1] 15.4324292 1.2769402 15.4433196 2.1640642 3.8189583 1.5256075 9.1251705 6.6026517
[9] 7.9725288 1.7822154 4.3544797 0.1876629 7.9384326 5.5563637 17.3626629 4.5010474
[17] 0.8047338 1.9163189 2.0870716 4.8703891 5.3728843 0.9691185 13.2630116 2.2297282
[25] 1.2678847 19.7409516 3.5037086 11.5733687 6.1511497 10.7581658 0.5721064 1.5974501
[33] 4.3027675 18.6710193 3.1457651 1.1578702 11.1287757 0.6880114 52.2844298 0.3066399
[41] 0.1721700 8.9232180 0.9650566 8.1402058 3.9502570 4.5482969 0.1992635 0.5191902
[49] 2.2159593 8.3779794 13.8463694 2.7443387 10.5041474 13.0338497 0.5867305 4.8797644
[57] 6.7521178 6.9591053 1.3149369 2.5724079 4.6739811 5.7231091 3.0620808 10.6264473
[65] 2.7166708 7.9099602 0.9176003 3.5792940 3.6920771 0.9274179 4.5079135 3.5476202
[73] 26.0471526 2.7161325 3.0995804 2.1983706 14.7653598 7.5426262 10.5156434 1.2381734
[81] 15.5187006 7.1937368 1.3900071 15.1256305 18.6899617 3.6014590 4.0216523 6.2863216
[89] 17.9072232 0.2829696 2.6308445 6.9573257 3.5342838 1.4393879 3.0780518 15.7667351
[97] 13.7706194 0.3386954 3.5021862 9.6589314
#Simulacion Variable Aleatoria Geometrica
> sim.geometrica(100,0.5)
[1] 1 8 0 9 2 1 1 3 2 0 1 0 1 1 0 1 1 4 0 3 2 2 1 2 2 1 2 3 1 2 2 1 1 8 2 0 3 5 1 0 0 1 1 1 1 0
[47] 1 0 0 0 3 0 2 0 3 2 2 1 4 2 3 0 2 1 3 0 0 0 0 3 2 2 2 3 0 2 0 0 0 2 1 0 1 0 1 2 0 1 4 1 1 1
[93] 5 1 3 1 0 6 0 1
#Simulacion Variable Aleatoria Hipergeometrica
> sim.hipergeometrica(200,100,40,20)
[1] 10 11 7 8 10 8 7 8 11 8 9 10 8 7 8 3 7 5 10 8 9 9 9 7 10 9 11 10 7 8 9
[32] 9 7 8 9 6 5 7 8 10 7 8 10 7 6 6 9 9 10 9 6 7 8 7 10 7 9 7 9 8 6 6
[63] 6 6 10 9 9 7 8 5 7 8 9 10 6 9 8 8 14 7 8 3 10 10 5 8 10 10 11 9 8 7 9
[94] 6 8 6 10 11 9 9 7 9 11 12 11 8 5 13 6 8 7 8 10 12 8 9 9 7 8 10 7 9 8 7
[125] 9 8 7 9 5 6 11 7 7 9 7 7 6 7 8 10 7 8 6 5 10 6 5 6 11 8 8 9 8 3 12
[156] 8 9 5 10 8 9 9 10 8 7 7 9 7 7 11 10 7 5 6 8 10 8 2 8 8 8 10 7 9 11 10
[187] 9 6 10 8 10 9 7 10 6 4 8 8 9 12
#Simulacion Variable Aleatoria Poisson
> sim.poisson(100,5)
[1] 6 7 6 10 8 5 5 3 11 4 3 1 2 6 5 1 5 6 4 6 4 7 6 3 9 5 5 5 8 7 5
[32] 2 7 8 6 3 3 6 5 3 5 5 3 5 5 6 2 3 1 4 5 7 5 2 3 4 5 2 8 4 3 1
[63] 4 6 7 2 5 4 3 4 3 7 12 8 4 6 9 7 3 6 2 5 10 4 9 4 3 6 4 8 6 4 6
[94] 5 9 5 4 4 8 4
#Simulacion Variable Aleatoria Normal via Box Muller
> snormalBM(100)
[1] "valores generados de X"
[1] -0.836680742 -0.057401114 -0.573398843 0.754762023 -0.437261617 -0.332083749 1.108383459
[8] 0.761701086 0.826051646 -0.078175210 -0.004688785 -0.991902188 0.082037217 0.860070269
[15] 0.853915365 1.483900844 -0.954793213 -1.312202719 0.737118418 -0.022660825 -0.644149454
[22] 0.058513309 -0.567826007 -1.005787672 1.181535114 0.965047970 0.636055737 -1.009742526
[29] 0.232625429 0.024014519 -0.092416763 -0.943287560 1.107459240 2.389261797 0.585759384
[36] 1.290600564 -1.775293517 1.188939781 0.930782380 -0.538232601 1.694010767 -0.256229014
[43] 0.539710912 -1.135554615 -1.678045427 0.030367331 -1.213657927 0.495888380 -0.248574755
[50] 0.045724561 1.345151416 2.369391584 0.200173414 0.693455138 0.938490863 -0.184914170
[57] 0.785580907 -0.858951585 -0.013480310 -1.228316278 -1.312838998 -2.039302105 -1.002131898
[64] -1.154906527 -0.276401421 1.130224441 -0.515162322 -0.553489687 0.328757876 -2.009848044
[71] 0.281643788 -0.900026698 0.564469273 1.084654692 -0.381010853 1.922786193 0.146210714
[78] 0.519156987 -0.646458512 -2.045164349 -0.238140910 -2.076021177 1.237339773 0.844925485
[85] -0.336980523 0.226823193 1.769405570 -0.932427870 -0.316653085 -1.771556000 -1.228566173
[92] 0.135906012 0.965531460 -0.663979508 1.826083452 -1.001738140 -0.900956689 1.629632064
[99] -1.174615882 0.096175840
[1] "valores generados de Y"
[1] -0.684181420 0.147229703 -0.741395388 0.432298263 -0.597438415 -0.213200849 -0.204589343
[8] 0.094486457 0.230360746 1.430605941 1.857869827 0.004002011 2.250335311 1.321564671
[15] -1.509705701 -1.391810500 -0.775684069 0.565501343 -0.049484857 -1.715369365 0.090989728
[22] 0.438660643 -1.305793481 2.350202203 0.283278517 -1.089557438 -0.644937928 1.191640643
[29] -0.514930868 -1.166183065 0.372592057 -0.372512301 -2.561631581 0.734849112 0.931334243
[36] -0.803162855 -0.992289133 1.563152982 1.485643403 -1.187867032 0.051498137 0.550909476
[43] -0.675419779 0.015924825 -1.760199776 0.727578348 -0.584647000 -1.181467653 -0.865116668
[50] 2.043304827 -0.994207017 -1.398184680 -1.298812504 0.827355489 0.555169336 0.038656586
[57] 2.094603381 0.100639918 -0.527041421 -1.878429249 -0.424218348 -1.884053392 2.185012587
[64] 0.437357013 0.489122416 -0.027847923 0.434183779 -1.926523219 -0.050705939 0.277681132
[71] -1.191116795 0.137938873 0.427321820 0.795417148 0.346833082 2.017914485 -0.688073429
[78] -1.790153355 0.751542305 1.198578826 -0.437270254 -1.024026502 0.914007532 0.121125566
[85] 1.307367713 -0.358811989 -1.629965345 -0.278873265 -0.443801248 -0.559606429 0.209004167
[92] -0.951212553 -1.397645130 -0.164417876 -1.430280799 -0.635262638 -0.491931625 -1.872534374
[99] -0.741437561 1.014920649
#Simulacion Variable Aleatoria Normal via Coordenadas Polares
> snormalCP(100)
[1] "valores generados de X"
[1] -1.42772745 1.48908537 -1.79767179 -0.35610168 -0.62741256 0.71544673 0.90265955
[8] -0.23938884 -0.28017809 -1.56070046 1.28680721 -1.26686810 0.74903114 -0.80738161
[15] 1.15218668 1.69231644 0.05639165 -0.57343673 -0.69412012 0.50155080 1.12770177
[22] -0.47608132 0.27250207 1.41653828 -1.12170907 -0.70885888 -0.58677575 0.52870682
[29] -0.72115323 1.49166229 -2.37221810 -0.27449933 -0.62082440 -1.85066055 -1.58060592
[36] -0.30481972 0.56015185 0.47632508 1.48649276 -0.37082691 -0.49954040 0.81735501
[43] 0.42878490 -1.09971084 -2.01224979 0.61624008 0.94615523 -0.09969550 -0.16090065
[50] 0.20035323 -0.37553658 1.29156725 0.83667896 2.19127476 -0.63666543 0.45457235
[57] 1.74345008 -1.13782822 -0.65264144 -1.72006628 -1.47404244 0.24198844 -0.24189256
[64] -0.42060676 1.38467143 0.25089719 -0.09394457 -0.46665753 -1.84992812 0.33958232
[71] -0.89938710 -0.80393199 -1.82044848 -1.18087195 1.13053855 0.45551755 -1.37179957
[78] -0.46902107 -1.08142251 1.89717818 1.29049339 -0.67800570 0.95724414 1.26204968
[85] 0.46286607 -0.71596384 0.71850168 -0.12525037 0.18443026 -1.61873804 0.43930073
[92] -1.98640020 0.21291018 2.01944426 1.43737175 -0.72044139 0.39808719 0.09604342
[99] -0.86227487 -0.58899200
[1] "valores generados de Y"
[1] -0.40262267 0.17302153 -0.85653006 0.44881078 0.10450577 -0.06512757 0.15400633
[8] -1.19307820 -1.85184740 0.69121591 0.13433273 -1.03541401 1.49995502 -0.87719119
[15] -1.22608479 -1.04680677 2.32296434 -0.66015318 2.57615133 1.23946927 1.14960237
[22] -0.28714177 -0.87278095 -0.14885293 -0.30134326 -1.90010766 -0.62253419 1.94309294
[29] -0.32898525 0.42185549 0.29046902 -0.27828834 0.54431764 -0.01988942 0.02685056
[36] 0.98045162 -0.44643650 -0.15878770 -0.63315742 -0.06788602 -0.52114597 -1.17261633
[43] 1.92363908 -0.22384496 -0.48641828 1.05994397 -1.04524715 1.43630599 0.58223555
[50] -0.07546200 0.31589475 0.70515550 0.05843099 1.10169321 -0.16154190 0.86513635
[57] 0.34519389 1.31943656 -1.54056641 -0.86777884 0.31394951 -0.37388777 -1.00003315
[64] -0.98030511 -1.08395038 0.06142717 1.11447805 0.15450985 -0.23843068 0.62013865
[71] 1.83062770 0.84917672 0.71102659 0.86187035 -0.28336571 0.17436825 0.09043334
[78] -1.31371110 0.23511116 -2.44798578 -0.11943985 -1.99362527 -0.06110943 1.55087167
[85] -0.55017294 -0.82821069 1.69195040 0.50343408 0.23723136 -0.07316155 -1.46784185
[92] -0.57299838 1.51780682 0.43787153 -0.33769026 -0.22066275 0.93748799 0.45979068
[99] 1.03553346 -0.8775717
Ver estas funcionalidades en el manual
Seomara Palominos (skpalominos@uc.cl)
Leonardo Jofré (lnjofre@uc.cl)
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