library(tidyverse)
## -- Attaching packages -------------------------------- tidyverse 1.2.1 --
## v ggplot2 3.3.0 v purrr 0.3.2
## v tibble 2.1.3 v dplyr 0.8.3
## v tidyr 1.0.0 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.4.0
## -- Conflicts ----------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(ggplot2)
library(readr)
library(maps)
##
## Attaching package: 'maps'
## The following object is masked from 'package:purrr':
##
## map
library(viridis)
## Loading required package: viridisLite
library(naivebayes)
## naivebayes 0.9.6 loaded
library(caret)
## Loading required package: lattice
##
## Attaching package: 'caret'
## The following object is masked from 'package:purrr':
##
## lift
library(e1071)
library(lattice)
chile<-read.csv2("covchile.csv")
chile
## FECHA INFECTADOS RECUPERADOR MUERTOS
## 1 lunes, 2 de marzo de 2020 0 0 0
## 2 martes, 3 de marzo de 2020 1 0 0
## 3 mi‚rcoles, 4 de marzo de 2020 1 0 0
## 4 jueves, 5 de marzo de 2020 4 0 0
## 5 viernes, 6 de marzo de 2020 4 0 0
## 6 s bado, 7 de marzo de 2020 4 0 0
## 7 domingo, 8 de marzo de 2020 8 0 0
## 8 lunes, 9 de marzo de 2020 8 0 0
## 9 martes, 10 de marzo de 2020 13 0 0
## 10 mi‚rcoles, 11 de marzo de 2020 23 0 0
## 11 jueves, 12 de marzo de 2020 23 0 0
## 12 viernes, 13 de marzo de 2020 43 0 0
## 13 s bado, 14 de marzo de 2020 61 0 0
## 14 domingo, 15 de marzo de 2020 74 0 0
## 15 lunes, 16 de marzo de 2020 155 0 0
boxplot(chile$INFECTADOS)
plot(chile$INFECTADOS)
summary(chile)
## FECHA INFECTADOS RECUPERADOR
## domingo, 15 de marzo de 2020:1 Min. : 0.00 Min. :0
## domingo, 8 de marzo de 2020 :1 1st Qu.: 4.00 1st Qu.:0
## jueves, 12 de marzo de 2020 :1 Median : 8.00 Median :0
## jueves, 5 de marzo de 2020 :1 Mean : 28.13 Mean :0
## lunes, 16 de marzo de 2020 :1 3rd Qu.: 33.00 3rd Qu.:0
## lunes, 2 de marzo de 2020 :1 Max. :155.00 Max. :0
## (Other) :9
## MUERTOS
## Min. :0
## 1st Qu.:0
## Median :0
## Mean :0
## 3rd Qu.:0
## Max. :0
##
library(githubinstall)
covid<-read.csv("../R STUDIO/03-16-2020.csv")
covid
## Province.State Country.Region
## 1 Hubei China
## 2 Italy
## 3 Iran
## 4 Spain
## 5 Korea, South
## 6 Germany
## 7 France France
## 8 Switzerland
## 9 United Kingdom United Kingdom
## 10 Netherlands Netherlands
## 11 Guangdong China
## 12 Norway
## 13 Henan China
## 14 Zhejiang China
## 15 Sweden
## 16 Belgium
## 17 Austria
## 18 Hunan China
## 19 Anhui China
## 20 New York US
## 21 Jiangxi China
## 22 Denmark Denmark
## 23 Washington US
## 24 Japan
## 25 Shandong China
## 26 Diamond Princess Cruise Ship
## 27 Jiangsu China
## 28 Chongqing China
## 29 Malaysia
## 30 California US
## 31 Sichuan China
## 32 Heilongjiang China
## 33 Beijing China
## 34 Qatar
## 35 Shanghai China
## 36 Greece
## 37 Portugal
## 38 Hebei China
## 39 Czechia
## 40 Fujian China
## 41 Finland
## 42 Israel
## 43 Slovenia
## 44 Guangxi China
## 45 Shaanxi China
## 46 Singapore
## 47 Bahrain
## 48 Estonia
## 49 Brazil
## 50 Massachusetts US
## 51 Iceland
## 52 New Jersey US
## 53 Ontario Canada
## 54 Poland
## 55 Yunnan China
## 56 New South Wales Australia
## 57 Ireland
## 58 Hainan China
## 59 Colorado US
## 60 Romania
## 61 Chile
## 62 Hong Kong China
## 63 Florida US
## 64 Egypt
## 65 Thailand
## 66 Guizhou China
## 67 Philippines
## 68 Tianjin China
## 69 Pakistan
## 70 Louisiana US
## 71 Indonesia
## 72 Gansu China
## 73 Shanxi China
## 74 Liaoning China
## 75 Iraq
## 76 Kuwait
## 77 Georgia US
## 78 India
## 79 Saudi Arabia
## 80 San Marino
## 81 Illinois US
## 82 British Columbia Canada
## 83 Lebanon
## 84 United Arab Emirates
## 85 Jilin China
## 86 Russia
## 87 Peru
## 88 Texas US
## 89 Luxembourg
## 90 Pennsylvania US
## 91 Xinjiang China
## 92 Inner Mongolia China
## 93 Ningxia China
## 94 Victoria Australia
## 95 Queensland Australia
## 96 Taiwan*
## 97 Slovakia
## 98 South Africa
## 99 Vietnam
## 100 Croatia
## 101 Argentina
## 102 Alberta Canada
## 103 Panama
## 104 Serbia
## 105 Algeria
## 106 Brunei
## 107 Colombia
## 108 Minnesota US
## 109 Mexico
## 110 Michigan US
## 111 Armenia
## 112 Bulgaria
## 113 Tennessee US
## 114 Albania
## 115 Quebec Canada
## 116 Ohio US
## 117 Virginia US
## 118 Diamond Princess US
## 119 Wisconsin US
## 120 Nevada US
## 121 Maryland US
## 122 Hungary
## 123 Oregon US
## 124 Utah US
## 125 North Carolina US
## 126 Ecuador
## 127 Belarus
## 128 Costa Rica
## 129 Latvia
## 130 Cyprus
## 131 Georgia
## 132 South Carolina US
## 133 Malta
## 134 Connecticut US
## 135 South Australia Australia
## 136 Morocco
## 137 Alabama US
## 138 Western Australia Australia
## 139 Sri Lanka
## 140 Bosnia and Herzegovina
## 141 Indiana US
## 142 Senegal
## 143 Moldova
## 144 Iowa US
## 145 Oman
## 146 Arkansas US
## 147 District of Columbia US
## 148 Afghanistan
## 149 Kentucky US
## 150 Rhode Island US
## 151 Tunisia
## 152 Grand Princess US
## 153 Qinghai China
## 154 Faroe Islands Denmark
## 155 North Macedonia
## 156 Turkey
## 157 Arizona US
## 158 Nebraska US
## 159 Jordan
## 160 Lithuania
## 161 Maine US
## 162 New Hampshire US
## 163 New Mexico US
## 164 Venezuela
## 165 Azerbaijan
## 166 Burkina Faso
## 167 Martinique
## 168 Maldives
## 169 Mississippi US
## 170 Vermont US
## 171 Bolivia
## 172 Macau China
## 173 Dominican Republic
## 174 French Guiana
## 175 Kansas US
## 176 Jamaica
## 177 Kazakhstan
## 178 Oklahoma US
## 179 South Dakota US
## 180 Reunion
## 181 Bangladesh
## 182 New Zealand
## 183 Paraguay
## 184 Delaware US
## 185 Uruguay
## 186 Tasmania Australia
## 187 Cambodia
## 188 Manitoba Canada
## 189 Saskatchewan Canada
## 190 Monaco
## 191 Hawaii US
## 192 Montana US
## 193 Ukraine
## 194 New Brunswick Canada
## 195 Ghana
## 196 Guadeloupe
## 197 Honduras
## 198 Missouri US
## 199 Channel Islands United Kingdom
## 200 Uzbekistan
## 201 Nova Scotia Canada
## 202 Ethiopia
## 203 French Guiana France
## 204 Rwanda
## 205 Idaho US
## 206 Puerto Rico US
## 207 Cameroon
## 208 Cuba
## 209 Guyana
## 210 Liechtenstein
## 211 Trinidad and Tobago
## 212 French Polynesia France
## 213 Guadeloupe France
## 214 Saint Barthelemy France
## 215 Guam
## 216 Kenya
## 217 Puerto Rico
## 218 Seychelles
## 219 Guam US
## 220 Wyoming US
## 221 Andorra
## 222 Aruba
## 223 Australian Capital Territory Australia
## 224 Grand Princess Canada
## 225 Congo (Kinshasa)
## 226 St Martin France
## 227 Guatemala
## 228 Jersey
## 229 Kosovo
## 230 Namibia
## 231 Nigeria
## 232 Saint Lucia
## 233 Antigua and Barbuda
## 234 Northern Territory Australia
## 235 Benin
## 236 Bhutan
## 237 Newfoundland and Labrador Canada
## 238 Prince Edward Island Canada
## 239 Central African Republic
## 240 Tibet China
## 241 Congo (Brazzaville)
## 242 Cote d'Ivoire
## 243 Equatorial Guinea
## 244 Eswatini
## 245 Mayotte France
## 246 Gabon
## 247 Greenland
## 248 Guernsey
## 249 Guinea
## 250 Holy See
## 251 Liberia
## 252 Mauritania
## 253 Mayotte
## 254 Mongolia
## 255 Nepal
## 256 Curacao Netherlands
## 257 Republic of the Congo
## 258 Saint Vincent and the Grenadines
## 259 Somalia
## 260 Sudan
## 261 Suriname
## 262 Tanzania
## 263 The Bahamas
## 264 Togo
## 265 Alaska US
## 266 North Dakota US
## 267 Virgin Islands US
## 268 Cayman Islands United Kingdom
## 269 Gibraltar United Kingdom
## 270 From Diamond Princess Australia
## 271 West Virginia US
## 272 occupied Palestinian territory
## Last.Update Confirmed Deaths Recovered Latitude Longitude
## 1 2020-03-16T14:38:45 67798 3099 55142 30.9756 112.2707
## 2 2020-03-16T17:33:03 27980 2158 2749 41.8719 12.5674
## 3 2020-03-16T14:38:45 14991 853 4590 32.4279 53.6880
## 4 2020-03-16T20:13:11 9942 342 530 40.4637 -3.7492
## 5 2020-03-16T14:38:45 8236 75 1137 35.9078 127.7669
## 6 2020-03-16T20:13:11 7272 17 67 51.1657 10.4515
## 7 2020-03-16T20:13:11 6633 148 12 46.2276 2.2137
## 8 2020-03-15T18:20:18 2200 14 4 46.8182 8.2275
## 9 2020-03-16T19:13:13 1543 55 20 55.3781 -3.4360
## 10 2020-03-16T14:38:46 1413 24 2 52.1326 5.2913
## 11 2020-03-16T01:53:03 1361 8 1306 23.3417 113.4244
## 12 2020-03-16T21:13:12 1333 3 1 60.4720 8.4689
## 13 2020-03-14T09:53:08 1273 22 1250 33.8820 113.6140
## 14 2020-03-16T14:38:45 1231 1 1216 29.1832 120.0934
## 15 2020-03-16T14:38:45 1103 6 1 60.1282 18.6435
## 16 2020-03-16T14:38:45 1058 5 1 50.5039 4.4699
## 17 2020-03-16T15:13:09 1018 3 6 47.5162 14.5501
## 18 2020-03-14T08:33:03 1018 4 1014 27.6104 111.7088
## 19 2020-03-11T02:18:14 990 6 984 31.8257 117.2264
## 20 2020-03-16T21:53:03 967 10 0 42.1657 -74.9481
## 21 2020-03-12T02:13:04 935 1 934 27.6140 115.7221
## 22 2020-03-16T18:33:03 914 3 1 56.2639 9.5018
## 23 2020-03-16T23:53:03 904 48 1 47.4009 -121.4905
## 24 2020-03-16T14:38:45 825 27 144 36.2048 138.2529
## 25 2020-03-16T14:38:45 760 7 746 36.3427 118.1498
## 26 2020-03-13T14:13:25 696 7 325 35.4498 139.6649
## 27 2020-03-15T01:53:02 631 0 631 32.9711 119.4550
## 28 2020-03-15T03:53:04 576 6 570 30.0572 107.8740
## 29 2020-03-16T14:38:45 566 0 42 4.2105 101.9758
## 30 2020-03-16T23:53:03 557 7 6 36.1162 -119.6816
## 31 2020-03-15T18:20:18 539 3 516 30.6171 102.7103
## 32 2020-03-16T14:38:45 482 13 455 47.8620 127.7615
## 33 2020-03-16T14:38:45 452 8 360 40.1824 116.4142
## 34 2020-03-16T15:13:09 439 0 4 25.3548 51.1839
## 35 2020-03-16T14:38:45 355 3 325 31.2020 121.4491
## 36 2020-03-16T00:22:10 331 4 8 39.0742 21.8243
## 37 2020-03-16T14:38:45 331 0 3 39.3999 -8.2245
## 38 2020-03-13T11:09:03 318 6 310 38.0428 114.5149
## 39 2020-03-16T23:53:02 298 0 3 49.8175 15.4730
## 40 2020-03-11T02:18:14 296 1 295 26.0789 117.9874
## 41 2020-03-16T14:38:45 277 0 10 61.9241 25.7482
## 42 2020-03-16T14:38:45 255 0 4 31.0461 34.8516
## 43 2020-03-16T14:38:45 253 1 0 46.1512 14.9955
## 44 2020-03-16T14:38:45 252 2 248 23.8298 108.7881
## 45 2020-03-16T14:38:45 245 2 233 35.1917 108.8701
## 46 2020-03-16T14:38:45 243 0 109 1.3521 103.8198
## 47 2020-03-16T20:33:03 214 1 77 26.0667 50.5577
## 48 2020-03-16T14:38:45 205 0 1 58.5953 25.0136
## 49 2020-03-16T02:33:08 200 0 1 -14.2350 -51.9253
## 50 2020-03-16T21:53:03 197 0 1 42.2302 -71.5301
## 51 2020-03-16T02:13:15 180 0 0 64.9631 -19.0208
## 52 2020-03-16T22:13:21 178 2 1 40.2989 -74.5210
## 53 2020-03-16T16:13:26 177 0 5 51.2538 -85.3232
## 54 2020-03-16T21:13:17 177 4 13 51.9194 19.1451
## 55 2020-03-16T23:53:02 176 2 172 24.9740 101.4870
## 56 2020-03-16T14:38:46 171 2 4 -33.8688 151.2093
## 57 2020-03-16T14:38:45 169 2 0 53.1424 -7.6921
## 58 2020-03-16T14:38:45 168 6 161 19.1959 109.7453
## 59 2020-03-16T23:53:03 160 1 0 39.0598 -105.3111
## 60 2020-03-16T14:38:45 158 0 9 45.9432 24.9668
## 61 2020-03-16T14:38:45 155 0 0 -35.6751 -71.5430
## 62 2020-03-16T14:38:45 155 4 84 22.3000 114.2000
## 63 2020-03-16T22:13:21 155 5 0 27.7663 -81.6868
## 64 2020-03-16T15:53:45 150 2 27 26.8206 30.8025
## 65 2020-03-16T14:38:45 147 1 35 15.8700 100.9925
## 66 2020-03-16T14:38:45 146 2 144 26.8154 106.8748
## 67 2020-03-16T14:38:45 142 12 2 12.8797 121.7740
## 68 2020-03-15T18:20:18 136 3 133 39.3054 117.3230
## 69 2020-03-16T14:38:45 136 0 2 30.3753 69.3451
## 70 2020-03-16T22:13:21 136 3 0 31.1695 -91.8678
## 71 2020-03-16T14:38:45 134 5 8 -0.7893 113.9213
## 72 2020-03-15T18:20:18 133 2 91 36.0611 103.8343
## 73 2020-03-13T11:09:03 133 0 133 37.5777 112.2922
## 74 2020-03-16T14:38:45 125 1 115 41.2956 122.6085
## 75 2020-03-16T02:13:15 124 10 26 33.2232 43.6793
## 76 2020-03-16T14:38:45 123 0 9 29.3117 47.4818
## 77 2020-03-16T16:53:06 121 1 0 33.0406 -83.6431
## 78 2020-03-16T14:38:45 119 2 13 20.5937 78.9629
## 79 2020-03-16T01:13:12 118 0 2 23.8859 45.0792
## 80 2020-03-16T01:33:03 109 7 4 43.9424 12.4578
## 81 2020-03-16T22:13:21 105 0 2 40.3495 -88.9861
## 82 2020-03-16T19:13:13 103 4 4 53.7267 -127.6476
## 83 2020-03-16T00:22:11 99 3 1 33.8547 35.8623
## 84 2020-03-16T00:22:11 98 0 23 23.4241 53.8478
## 85 2020-03-16T00:22:10 93 1 92 43.6661 126.1923
## 86 2020-03-16T14:38:45 90 0 8 61.5240 105.3188
## 87 2020-03-16T14:38:45 86 0 0 -9.1900 -75.0152
## 88 2020-03-16T23:53:03 85 0 0 31.0545 -97.5635
## 89 2020-03-16T01:53:03 77 1 0 49.8153 6.1296
## 90 2020-03-16T20:13:20 77 0 0 40.5908 -77.2098
## 91 2020-03-11T02:18:14 76 3 73 41.1129 85.2401
## 92 2020-03-16T14:38:45 75 1 73 44.0935 113.9448
## 93 2020-03-16T14:38:45 75 0 75 37.2692 106.1655
## 94 2020-03-16T14:38:45 71 0 8 -37.8136 144.9631
## 95 2020-03-16T14:38:46 68 0 8 -28.0167 153.4000
## 96 2020-03-16T14:38:45 67 1 20 23.7000 121.0000
## 97 2020-03-16T14:38:45 63 0 0 48.6690 19.6990
## 98 2020-03-16T14:38:45 62 0 0 -30.5595 22.9375
## 99 2020-03-16T14:53:04 61 0 16 14.0583 108.2772
## 100 2020-03-16T14:38:45 57 0 2 45.1000 15.2000
## 101 2020-03-16T14:38:45 56 2 1 -38.4161 -63.6167
## 102 2020-03-16T02:33:09 56 0 0 53.9333 -116.5765
## 103 2020-03-16T14:38:45 55 1 0 8.5380 -80.7821
## 104 2020-03-16T14:38:45 55 0 1 44.0165 21.0059
## 105 2020-03-16T14:38:45 54 4 12 28.0339 1.6596
## 106 2020-03-16T14:38:45 54 0 0 4.5353 114.7277
## 107 2020-03-16T14:38:45 54 0 0 4.5709 -74.2973
## 108 2020-03-16T16:53:06 54 0 0 45.6945 -93.9002
## 109 2020-03-16T14:38:45 53 0 4 23.6345 -102.5528
## 110 2020-03-16T14:38:46 53 0 0 43.3266 -84.5361
## 111 2020-03-16T21:13:17 52 0 0 40.0691 45.0382
## 112 2020-03-16T14:38:45 52 2 0 42.7339 25.4858
## 113 2020-03-16T22:13:21 52 0 0 35.7478 -86.6923
## 114 2020-03-16T14:38:45 51 1 0 41.1533 20.1683
## 115 2020-03-16T20:13:20 50 0 0 52.9399 -73.5491
## 116 2020-03-16T20:13:21 50 0 0 40.3888 -82.7649
## 117 2020-03-16T22:13:21 49 1 0 37.7693 -78.1700
## 118 2020-03-16T16:53:06 47 0 0 35.4437 139.6380
## 119 2020-03-16T20:13:20 47 0 1 44.2685 -89.6165
## 120 2020-03-16T20:13:20 45 1 0 38.3135 -117.0554
## 121 2020-03-16T20:13:20 41 0 3 39.0639 -76.8021
## 122 2020-03-16T14:38:45 39 1 1 47.1625 19.5033
## 123 2020-03-16T02:33:09 39 1 0 44.5720 -122.0709
## 124 2020-03-16T22:33:03 39 0 0 40.1500 -111.8624
## 125 2020-03-16T23:53:03 38 0 0 35.6301 -79.8064
## 126 2020-03-16T02:33:08 37 2 0 -1.8312 -78.1834
## 127 2020-03-16T14:38:45 36 0 3 53.7098 27.9534
## 128 2020-03-16T02:33:08 35 0 0 9.7489 -83.7534
## 129 2020-03-16T14:38:45 34 0 1 56.8796 24.6032
## 130 2020-03-16T02:33:08 33 0 0 35.1264 33.4299
## 131 2020-03-16T02:13:16 33 0 1 42.3154 43.3569
## 132 2020-03-16T22:33:03 33 1 0 33.8569 -80.9450
## 133 2020-03-16T15:33:03 30 0 2 35.9375 14.3754
## 134 2020-03-16T20:13:20 30 0 0 41.5978 -72.7554
## 135 2020-03-16T14:38:46 29 0 3 -34.9285 138.6007
## 136 2020-03-16T14:38:45 29 1 1 31.7917 -7.0926
## 137 2020-03-16T22:33:03 29 0 0 32.3182 -86.9023
## 138 2020-03-16T14:38:46 28 1 0 -31.9505 115.8605
## 139 2020-03-16T15:53:45 28 0 1 7.8731 80.7718
## 140 2020-03-16T21:13:17 25 0 0 43.9159 17.6791
## 141 2020-03-16T22:33:03 25 1 0 39.8494 -86.2583
## 142 2020-03-16T01:13:13 24 0 2 14.4974 -14.4524
## 143 2020-03-16T00:22:11 23 0 0 47.4116 28.3699
## 144 2020-03-16T23:53:03 23 0 0 42.0115 -93.2105
## 145 2020-03-16T00:22:11 22 0 9 21.4735 55.9754
## 146 2020-03-16T17:13:23 22 0 0 34.9697 -92.3731
## 147 2020-03-16T23:53:03 22 0 0 38.8974 -77.0268
## 148 2020-03-16T14:38:45 21 0 1 33.9391 67.7100
## 149 2020-03-16T18:33:03 21 1 1 37.6681 -84.6701
## 150 2020-03-16T18:14:12 21 0 0 41.6809 -71.5118
## 151 2020-03-16T01:13:13 20 0 0 33.8869 9.5375
## 152 2020-03-16T17:13:23 20 0 0 37.6489 -122.6655
## 153 2020-03-11T02:18:14 18 0 18 35.7452 95.9956
## 154 2020-03-16T14:38:45 18 0 0 61.8926 -6.9118
## 155 2020-03-16T14:38:45 18 0 1 41.6086 21.7453
## 156 2020-03-16T01:13:13 18 0 0 38.9637 35.2433
## 157 2020-03-16T17:13:23 18 0 1 33.7298 -111.4312
## 158 2020-03-16T17:13:23 18 0 0 41.1254 -98.2681
## 159 2020-03-16T15:13:35 17 0 1 30.5852 36.2384
## 160 2020-03-16T14:38:45 17 0 1 55.1694 23.8813
## 161 2020-03-16T18:14:12 17 0 0 44.6939 -69.3819
## 162 2020-03-16T22:33:03 17 0 0 43.4525 -71.5639
## 163 2020-03-16T02:53:12 17 0 0 34.8405 -106.2485
## 164 2020-03-16T00:53:03 17 0 0 6.4238 -66.5897
## 165 2020-03-16T14:38:45 15 1 6 40.1431 47.5769
## 166 2020-03-16T14:38:45 15 0 0 12.2383 -1.5616
## 167 2020-03-16T14:38:45 15 1 0 14.6415 -61.0242
## 168 2020-03-15T18:20:18 13 0 0 3.2028 73.2207
## 169 2020-03-16T22:33:03 13 0 0 32.7416 -89.6787
## 170 2020-03-16T17:13:23 12 0 0 44.0459 -72.7107
## 171 2020-03-16T14:38:45 11 0 0 -16.2902 -63.5887
## 172 2020-03-16T00:22:10 11 0 10 22.1667 113.5500
## 173 2020-03-14T20:53:02 11 0 0 18.7357 -70.1627
## 174 2020-03-16T14:38:46 11 0 0 3.9339 -53.1258
## 175 2020-03-16T17:13:23 11 1 0 38.5266 -96.7265
## 176 2020-03-16T01:53:03 10 0 2 18.1096 -77.2975
## 177 2020-03-16T14:38:45 10 0 0 48.0196 66.9237
## 178 2020-03-16T18:14:12 10 0 0 35.5653 -96.9289
## 179 2020-03-16T20:13:20 10 1 0 44.2998 -99.4388
## 180 2020-03-16T14:38:45 9 0 0 -21.1151 55.5364
## 181 2020-03-16T14:38:45 8 0 2 23.6850 90.3563
## 182 2020-03-15T18:20:18 8 0 0 -40.9006 174.8860
## 183 2020-03-16T14:38:45 8 0 0 -23.4425 -58.4438
## 184 2020-03-16T20:13:20 8 0 0 39.3185 -75.5071
## 185 2020-03-16T14:38:45 8 0 0 -32.5228 -55.7658
## 186 2020-03-16T14:38:46 7 0 0 -41.4545 145.9707
## 187 2020-03-14T12:53:07 7 0 1 12.5657 104.9910
## 188 2020-03-16T02:53:12 7 0 0 53.7609 -98.8139
## 189 2020-03-16T20:13:20 7 0 0 52.9399 -106.4509
## 190 2020-03-16T14:38:45 7 0 0 43.7384 7.4246
## 191 2020-03-16T02:53:12 7 0 0 21.0943 -157.4983
## 192 2020-03-15T18:20:19 7 0 0 46.9219 -110.4544
## 193 2020-03-16T21:13:17 7 1 0 48.3794 31.1656
## 194 2020-03-16T02:53:12 6 0 0 46.5653 -66.4619
## 195 2020-03-15T18:20:18 6 0 0 7.9465 -1.0232
## 196 2020-03-16T14:38:45 6 0 0 16.2650 -61.5510
## 197 2020-03-16T14:38:45 6 0 0 15.2000 -86.2419
## 198 2020-03-16T17:13:23 6 0 0 38.4561 -92.2884
## 199 2020-03-16T14:38:45 6 0 0 49.3723 -2.3644
## 200 2020-03-16T14:38:45 6 0 0 41.3775 64.5853
## 201 2020-03-16T17:53:03 5 0 0 44.6820 -63.7443
## 202 2020-03-16T14:38:45 5 0 0 9.1450 40.4897
## 203 2020-03-16T14:38:45 5 0 0 4.0000 -53.0000
## 204 2020-03-16T01:33:03 5 0 0 -1.9403 29.8739
## 205 2020-03-15T18:20:19 5 0 0 44.2405 -114.4788
## 206 2020-03-16T00:22:11 5 0 0 18.2208 -66.5901
## 207 2020-03-16T02:33:08 4 0 0 3.8480 11.5021
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## 218 2020-03-16T01:13:13 3 0 0 -4.6796 55.4920
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## 243 2020-03-15T06:41:54 1 0 0 1.5000 10.0000
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## 257 2020-03-16T03:33:03 1 0 0 -1.4400 15.5560
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## 259 2020-03-16T14:38:46 1 0 0 5.1521 46.1996
## 260 2020-03-14T01:13:32 1 1 0 12.8628 30.2176
## 261 2020-03-14T16:33:03 1 0 0 3.9193 -56.0278
## 262 2020-03-16T14:38:45 1 0 0 -6.3690 34.8888
## 263 2020-03-16T03:33:03 1 0 0 24.2500 -76.0000
## 264 2020-03-13T22:22:02 1 0 0 8.6195 0.8248
## 265 2020-03-13T14:53:03 1 0 0 61.3707 -152.4044
## 266 2020-03-12T09:33:03 1 0 0 47.5289 -99.7840
## 267 2020-03-16T00:22:11 1 0 0 18.3358 -64.8963
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## 269 2020-03-14T16:33:03 1 0 1 36.1408 -5.3536
## 270 2020-03-14T02:33:04 0 0 0 35.4437 139.6380
## 271 2020-03-10T02:33:04 0 0 0 38.4912 -80.9545
## 272 2020-03-11T20:53:02 0 0 0 31.9522 35.2332
library(ggplot2)
muerteCOVID<-covid[, 4:5]
ggplot(muerteCOVID, aes(x=Confirmed, y=Deaths)) + geom_point()
library(neuralnet)
##
## Attaching package: 'neuralnet'
## The following object is masked from 'package:dplyr':
##
## compute
maxs <- apply(muerteCOVID, 2, max) # Máximo valor de las variables
mins <- apply(muerteCOVID, 2, min) # Mínimo valor de las variables
scaled <- as.data.frame(scale(muerteCOVID, center=mins, scale=maxs-mins))
head(cbind(muerteCOVID, scaled))
## Confirmed Deaths Confirmed Deaths
## 1 67798 3099 1.0000000 1.000000000
## 2 27980 2158 0.4126965 0.696353662
## 3 14991 853 0.2211127 0.275250081
## 4 9942 342 0.1466415 0.110358180
## 5 8236 75 0.1214785 0.024201355
## 6 7272 17 0.1072598 0.005485641
library(gridExtra)
##
## Attaching package: 'gridExtra'
## The following object is masked from 'package:dplyr':
##
## combine
plot1 <- ggplot(muerteCOVID, aes(x=Confirmed, y=Deaths)) + geom_point()
plot2 <- ggplot(scaled, aes(x=Confirmed, y=Deaths)) + geom_point()
grid.arrange(plot1, plot2, ncol=2)
library(neuralnet)
mod1 <- neuralnet(Deaths ~ Confirmed, data=scaled, hidden=c(3), threshold=0.01)
plot(mod1, rep="best")
names(mod1) # Elementos que tiene al interior mod1
## [1] "call" "response" "covariate"
## [4] "model.list" "err.fct" "act.fct"
## [7] "linear.output" "data" "exclude"
## [10] "net.result" "weights" "generalized.weights"
## [13] "startweights" "result.matrix"
Predicción
test <- data.frame(Deaths = scaled$Deaths)
myprediction <- compute(x=mod1, covariate=test)
myprediction$net.result[1:5] # Esto esta como escalar, se vuelve a su forma original
## [1] 1.009606624 1.014730640 0.378897628 0.044255734 0.003893118
#confirmados
yhat_red <- myprediction$net.result * (max(muerteCOVID$Confirmed)-min(muerteCOVID$Confirmed))+min(muerteCOVID$Confirmed)
muerteCOVID$yhat_red <- yhat_red
yhat_red[1:5]
## [1] 68449.3099 68796.7079 25688.5014 3000.4503 263.9456
#muertos
yhat_red <- myprediction$net.result * (max(muerteCOVID$Deaths)-min(muerteCOVID$Deaths))+min(muerteCOVID$Deaths)
muerteCOVID$yhat_red <- yhat_red
yhat_red[1:5]
## [1] 3128.77093 3144.65025 1174.20375 137.14852 12.06477
H0: NO ES PANDEMIA YA QUE POSEE DISTRIBUCIÓN GAUSSIANA
RECHAZO DE H0, CLARAMENTE EL MODELO NO ES FACTIBLE, YA QUE ESTAMOS TRATANDO CON UNA DISTRIBUCIÓN EXPONENCIAL O SIMILAR *** ESTO DEMUESTRA EL EFECTO DE PANDEMIA ***
ggplot(muerteCOVID, aes(x=Confirmed, y=yhat_red)) + geom_point() +
geom_abline(intercept=0, slope=1, color="blue", linetype="dashed", size=1.5)
