as.fd: Frequency distribution of a precipitation serie
In precintcon: Precipitation Intensity, Concentration and Anomaly Analysis
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
Description
Calculates the frequency distribution of a daily precipitation
serie based on interval.
Usage
1
as.precintcon.fd(object, interval = 1)
Arguments
object
a daily precipitation serie.
interval
the interval in millimeters for calculating the frequency
distribution.
Value
A data.frame (precintcon.fd) containing the following variables:
-
initial.class is the initial value of the class.
-
final.class is the final value of the class.
-
midpoint is the middle point of the class.
-
n is the absolute freqnecy, i.e., the number of days in each
class.
-
sum.n is the cumulative frequency, obtained by adding the absolute
frequencies of all the classes up to the one under consideration.
-
P is the pluviometric total of each class, obtained by multiplying
midpoint by n.
-
sum.P is the cummulative class's pluviometric total, obtained by
adding the pluviometric total of all the classes up to the one under consideration.
-
p.sum.n is the cumulative percentage of rainy days.
-
p.sum.P is the cumulative percentage of rainfall amounts.
Author(s)
Lucas Venezian Povoa lucasvenez@gmail.com
See Also
Examples
1
2
3
4
5
6
7
##
# Loading the daily precipitation serie
data(daily)
##
# Performing the frequency distribution
as.precintcon.fd(daily)
Example output
Loading required package: ggplot2
Loading required package: scales
Attaching package: 'precintcon'
The following object is masked from 'package:ggplot2':
stat
initial.class final.class midpoint n sum.n P sum.P p.sum.n
1 1 1.9 1.5 115 115 172.5 172.5 0.04459093
2 2 2.9 2.5 154 269 385.0 557.5 0.10430399
3 3 3.9 3.5 129 398 451.5 1009.0 0.15432338
4 4 4.9 4.5 130 528 585.0 1594.0 0.20473052
5 5 5.9 5.5 136 664 748.0 2342.0 0.25746413
6 6 6.9 6.5 114 778 741.0 3083.0 0.30166731
7 7 7.9 7.5 86 864 645.0 3728.0 0.33501357
8 8 8.9 8.5 96 960 816.0 4544.0 0.37223730
9 9 9.9 9.5 88 1048 836.0 5380.0 0.40635905
10 10 10.9 10.5 104 1152 1092.0 6472.0 0.44668476
11 11 11.9 11.5 84 1236 966.0 7438.0 0.47925553
12 12 12.9 12.5 73 1309 912.5 8350.5 0.50756107
13 13 13.9 13.5 65 1374 877.5 9228.0 0.53276464
14 14 14.9 14.5 65 1439 942.5 10170.5 0.55796820
15 15 15.9 15.5 71 1510 1100.5 11271.0 0.58549826
16 16 16.9 16.5 53 1563 874.5 12145.5 0.60604886
17 17 17.9 17.5 57 1620 997.5 13143.0 0.62815045
18 18 18.9 18.5 65 1685 1202.5 14345.5 0.65335401
19 19 19.9 19.5 48 1733 936.0 15281.5 0.67196588
20 20 20.9 20.5 53 1786 1086.5 16368.0 0.69251648
21 21 21.9 21.5 39 1825 838.5 17206.5 0.70763862
22 22 22.9 22.5 38 1863 855.0 18061.5 0.72237301
23 23 23.9 23.5 40 1903 940.0 19001.5 0.73788290
24 24 24.9 24.5 45 1948 1102.5 20104.0 0.75533152
25 25 25.9 25.5 48 1996 1224.0 21328.0 0.77394339
26 26 26.9 26.5 24 2020 636.0 21964.0 0.78324932
27 27 27.9 27.5 28 2048 770.0 22734.0 0.79410624
28 28 28.9 28.5 32 2080 912.0 23646.0 0.80651415
29 29 29.9 29.5 21 2101 619.5 24265.5 0.81465684
30 30 30.9 30.5 40 2141 1220.0 25485.5 0.83016673
31 31 31.9 31.5 24 2165 756.0 26241.5 0.83947266
32 32 32.9 32.5 17 2182 552.5 26794.0 0.84606437
33 33 33.9 33.5 21 2203 703.5 27497.5 0.85420706
34 34 34.9 34.5 16 2219 552.0 28049.5 0.86041101
35 35 35.9 35.5 28 2247 994.0 29043.5 0.87126793
36 36 36.9 36.5 13 2260 474.5 29518.0 0.87630865
37 37 37.9 37.5 18 2278 675.0 30193.0 0.88328810
38 38 38.9 38.5 17 2295 654.5 30847.5 0.88987980
39 39 39.9 39.5 20 2315 790.0 31637.5 0.89763474
40 40 40.9 40.5 19 2334 769.5 32407.0 0.90500194
41 41 41.9 41.5 19 2353 788.5 33195.5 0.91236914
42 42 42.9 42.5 11 2364 467.5 33663.0 0.91663435
43 43 43.9 43.5 4 2368 174.0 33837.0 0.91818534
44 44 44.9 44.5 14 2382 623.0 34460.0 0.92361380
45 45 45.9 45.5 15 2397 682.5 35142.5 0.92943001
46 46 46.9 46.5 5 2402 232.5 35375.0 0.93136875
47 47 47.9 47.5 9 2411 427.5 35802.5 0.93485847
48 48 48.9 48.5 11 2422 533.5 36336.0 0.93912369
49 49 49.9 49.5 8 2430 396.0 36732.0 0.94222567
50 50 50.9 50.5 15 2445 757.5 37489.5 0.94804188
51 51 51.9 51.5 11 2456 566.5 38056.0 0.95230710
52 52 52.9 52.5 5 2461 262.5 38318.5 0.95424583
53 53 53.9 53.5 8 2469 428.0 38746.5 0.95734781
54 54 54.9 54.5 2 2471 109.0 38855.5 0.95812330
55 55 55.9 55.5 2 2473 111.0 38966.5 0.95889880
56 56 56.9 56.5 5 2478 282.5 39249.0 0.96083753
57 57 57.9 57.5 4 2482 230.0 39479.0 0.96238852
58 58 58.9 58.5 7 2489 409.5 39888.5 0.96510275
59 59 59.9 59.5 7 2496 416.5 40305.0 0.96781698
60 60 60.9 60.5 5 2501 302.5 40607.5 0.96975572
61 61 61.9 61.5 4 2505 246.0 40853.5 0.97130671
62 62 62.9 62.5 3 2508 187.5 41041.0 0.97246995
63 63 63.9 63.5 3 2511 190.5 41231.5 0.97363319
64 64 64.9 64.5 5 2516 322.5 41554.0 0.97557193
65 65 65.9 65.5 3 2519 196.5 41750.5 0.97673517
66 66 66.9 66.5 3 2522 199.5 41950.0 0.97789841
67 67 67.9 67.5 3 2525 202.5 42152.5 0.97906165
68 68 68.9 68.5 2 2527 137.0 42289.5 0.97983715
69 69 69.9 69.5 4 2531 278.0 42567.5 0.98138813
70 70 70.9 70.5 2 2533 141.0 42708.5 0.98216363
71 71 71.9 71.5 3 2536 214.5 42923.0 0.98332687
72 72 72.9 72.5 2 2538 145.0 43068.0 0.98410237
73 73 73.9 73.5 3 2541 220.5 43288.5 0.98526561
74 74 74.9 74.5 4 2545 298.0 43586.5 0.98681660
75 75 75.9 75.5 3 2548 226.5 43813.0 0.98797984
76 77 77.9 77.5 1 2549 77.5 43890.5 0.98836758
77 79 79.9 79.5 1 2550 79.5 43970.0 0.98875533
78 80 80.9 80.5 2 2552 161.0 44131.0 0.98953083
79 81 81.9 81.5 1 2553 81.5 44212.5 0.98991857
80 82 82.9 82.5 1 2554 82.5 44295.0 0.99030632
81 83 83.9 83.5 2 2556 167.0 44462.0 0.99108181
82 84 84.9 84.5 2 2558 169.0 44631.0 0.99185731
83 85 85.9 85.5 1 2559 85.5 44716.5 0.99224506
84 86 86.9 86.5 2 2561 173.0 44889.5 0.99302055
85 87 87.9 87.5 1 2562 87.5 44977.0 0.99340830
86 90 90.9 90.5 1 2563 90.5 45067.5 0.99379604
87 93 93.9 93.5 2 2565 187.0 45254.5 0.99457154
88 94 94.9 94.5 2 2567 189.0 45443.5 0.99534703
89 96 96.9 96.5 1 2568 96.5 45540.0 0.99573478
90 98 98.9 98.5 1 2569 98.5 45638.5 0.99612253
91 99 99.9 99.5 1 2570 99.5 45738.0 0.99651028
92 103 103.9 103.5 2 2572 207.0 45945.0 0.99728577
93 105 105.9 105.5 1 2573 105.5 46050.5 0.99767352
94 106 106.9 106.5 1 2574 106.5 46157.0 0.99806126
95 107 107.9 107.5 1 2575 107.5 46264.5 0.99844901
96 117 117.9 117.5 1 2576 117.5 46382.0 0.99883676
97 120 120.9 120.5 1 2577 120.5 46502.5 0.99922451
98 150 150.9 150.5 1 2578 150.5 46653.0 0.99961225
99 151 151.9 151.5 1 2579 151.5 46804.5 1.00000000
p.sum.P
1 0.003685543
2 0.011911248
3 0.021557756
4 0.034056554
5 0.050037924
6 0.065869735
7 0.079650461
8 0.097084682
9 0.114946212
10 0.138277302
11 0.158916344
12 0.178412332
13 0.197160529
14 0.217297482
15 0.240810179
16 0.259494279
17 0.280806333
18 0.306498307
19 0.326496384
20 0.349709964
21 0.367624908
22 0.385892382
23 0.405975921
24 0.429531348
25 0.455682680
26 0.469271117
27 0.485722527
28 0.505207833
29 0.518443739
30 0.544509609
31 0.560661902
32 0.572466323
33 0.587496929
34 0.599290666
35 0.620527941
36 0.630665855
37 0.645087545
38 0.659071243
39 0.675949962
40 0.692390689
41 0.709237360
42 0.719225715
43 0.722943307
44 0.736253993
45 0.750835924
46 0.755803395
47 0.764937132
48 0.776335609
49 0.784796334
50 0.800980675
51 0.813084212
52 0.818692647
53 0.827837067
54 0.830165903
55 0.832537470
56 0.838573214
57 0.843487272
58 0.852236430
59 0.861135147
60 0.867598201
61 0.872854106
62 0.876860131
63 0.880930252
64 0.887820616
65 0.892018930
66 0.896281340
67 0.900607848
68 0.903534917
69 0.909474516
70 0.912487047
71 0.917069940
72 0.920167933
73 0.924879018
74 0.931245927
75 0.936085205
76 0.937741029
77 0.939439584
78 0.942879424
79 0.944620710
80 0.946383361
81 0.949951394
82 0.953562157
83 0.955388905
84 0.959085131
85 0.960954609
86 0.962888184
87 0.966883526
88 0.970921599
89 0.972983367
90 0.975087865
91 0.977213729
92 0.981636381
93 0.983890438
94 0.986165860
95 0.988462648
96 0.990973090
97 0.993547629
98 0.996763132
99 1.000000000
precintcon documentation built on May 2, 2019, 3:07 p.m.
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Description Usage Arguments Value Author(s) See Also Examples
Description
Calculates the frequency distribution of a daily precipitation
serie based on interval.
Usage
1 | as.precintcon.fd(object, interval = 1)
|
Arguments
object |
a daily precipitation serie. |
interval |
the interval in millimeters for calculating the frequency distribution. |
Value
A data.frame (precintcon.fd) containing the following variables:
-
initial.classis the initial value of the class. -
final.classis the final value of the class. -
midpointis the middle point of the class. -
nis the absolute freqnecy, i.e., the number of days in each class. -
sum.nis the cumulative frequency, obtained by adding the absolute frequencies of all the classes up to the one under consideration. -
Pis the pluviometric total of each class, obtained by multiplyingmidpointbyn. -
sum.Pis the cummulative class's pluviometric total, obtained by adding the pluviometric total of all the classes up to the one under consideration. -
p.sum.nis the cumulative percentage of rainy days. -
p.sum.Pis the cumulative percentage of rainfall amounts.
Author(s)
Lucas Venezian Povoa lucasvenez@gmail.com
See Also
Examples
1 2 3 4 5 6 7 | ##
# Loading the daily precipitation serie
data(daily)
##
# Performing the frequency distribution
as.precintcon.fd(daily)
|
Example output
Loading required package: ggplot2
Loading required package: scales
Attaching package: 'precintcon'
The following object is masked from 'package:ggplot2':
stat
initial.class final.class midpoint n sum.n P sum.P p.sum.n
1 1 1.9 1.5 115 115 172.5 172.5 0.04459093
2 2 2.9 2.5 154 269 385.0 557.5 0.10430399
3 3 3.9 3.5 129 398 451.5 1009.0 0.15432338
4 4 4.9 4.5 130 528 585.0 1594.0 0.20473052
5 5 5.9 5.5 136 664 748.0 2342.0 0.25746413
6 6 6.9 6.5 114 778 741.0 3083.0 0.30166731
7 7 7.9 7.5 86 864 645.0 3728.0 0.33501357
8 8 8.9 8.5 96 960 816.0 4544.0 0.37223730
9 9 9.9 9.5 88 1048 836.0 5380.0 0.40635905
10 10 10.9 10.5 104 1152 1092.0 6472.0 0.44668476
11 11 11.9 11.5 84 1236 966.0 7438.0 0.47925553
12 12 12.9 12.5 73 1309 912.5 8350.5 0.50756107
13 13 13.9 13.5 65 1374 877.5 9228.0 0.53276464
14 14 14.9 14.5 65 1439 942.5 10170.5 0.55796820
15 15 15.9 15.5 71 1510 1100.5 11271.0 0.58549826
16 16 16.9 16.5 53 1563 874.5 12145.5 0.60604886
17 17 17.9 17.5 57 1620 997.5 13143.0 0.62815045
18 18 18.9 18.5 65 1685 1202.5 14345.5 0.65335401
19 19 19.9 19.5 48 1733 936.0 15281.5 0.67196588
20 20 20.9 20.5 53 1786 1086.5 16368.0 0.69251648
21 21 21.9 21.5 39 1825 838.5 17206.5 0.70763862
22 22 22.9 22.5 38 1863 855.0 18061.5 0.72237301
23 23 23.9 23.5 40 1903 940.0 19001.5 0.73788290
24 24 24.9 24.5 45 1948 1102.5 20104.0 0.75533152
25 25 25.9 25.5 48 1996 1224.0 21328.0 0.77394339
26 26 26.9 26.5 24 2020 636.0 21964.0 0.78324932
27 27 27.9 27.5 28 2048 770.0 22734.0 0.79410624
28 28 28.9 28.5 32 2080 912.0 23646.0 0.80651415
29 29 29.9 29.5 21 2101 619.5 24265.5 0.81465684
30 30 30.9 30.5 40 2141 1220.0 25485.5 0.83016673
31 31 31.9 31.5 24 2165 756.0 26241.5 0.83947266
32 32 32.9 32.5 17 2182 552.5 26794.0 0.84606437
33 33 33.9 33.5 21 2203 703.5 27497.5 0.85420706
34 34 34.9 34.5 16 2219 552.0 28049.5 0.86041101
35 35 35.9 35.5 28 2247 994.0 29043.5 0.87126793
36 36 36.9 36.5 13 2260 474.5 29518.0 0.87630865
37 37 37.9 37.5 18 2278 675.0 30193.0 0.88328810
38 38 38.9 38.5 17 2295 654.5 30847.5 0.88987980
39 39 39.9 39.5 20 2315 790.0 31637.5 0.89763474
40 40 40.9 40.5 19 2334 769.5 32407.0 0.90500194
41 41 41.9 41.5 19 2353 788.5 33195.5 0.91236914
42 42 42.9 42.5 11 2364 467.5 33663.0 0.91663435
43 43 43.9 43.5 4 2368 174.0 33837.0 0.91818534
44 44 44.9 44.5 14 2382 623.0 34460.0 0.92361380
45 45 45.9 45.5 15 2397 682.5 35142.5 0.92943001
46 46 46.9 46.5 5 2402 232.5 35375.0 0.93136875
47 47 47.9 47.5 9 2411 427.5 35802.5 0.93485847
48 48 48.9 48.5 11 2422 533.5 36336.0 0.93912369
49 49 49.9 49.5 8 2430 396.0 36732.0 0.94222567
50 50 50.9 50.5 15 2445 757.5 37489.5 0.94804188
51 51 51.9 51.5 11 2456 566.5 38056.0 0.95230710
52 52 52.9 52.5 5 2461 262.5 38318.5 0.95424583
53 53 53.9 53.5 8 2469 428.0 38746.5 0.95734781
54 54 54.9 54.5 2 2471 109.0 38855.5 0.95812330
55 55 55.9 55.5 2 2473 111.0 38966.5 0.95889880
56 56 56.9 56.5 5 2478 282.5 39249.0 0.96083753
57 57 57.9 57.5 4 2482 230.0 39479.0 0.96238852
58 58 58.9 58.5 7 2489 409.5 39888.5 0.96510275
59 59 59.9 59.5 7 2496 416.5 40305.0 0.96781698
60 60 60.9 60.5 5 2501 302.5 40607.5 0.96975572
61 61 61.9 61.5 4 2505 246.0 40853.5 0.97130671
62 62 62.9 62.5 3 2508 187.5 41041.0 0.97246995
63 63 63.9 63.5 3 2511 190.5 41231.5 0.97363319
64 64 64.9 64.5 5 2516 322.5 41554.0 0.97557193
65 65 65.9 65.5 3 2519 196.5 41750.5 0.97673517
66 66 66.9 66.5 3 2522 199.5 41950.0 0.97789841
67 67 67.9 67.5 3 2525 202.5 42152.5 0.97906165
68 68 68.9 68.5 2 2527 137.0 42289.5 0.97983715
69 69 69.9 69.5 4 2531 278.0 42567.5 0.98138813
70 70 70.9 70.5 2 2533 141.0 42708.5 0.98216363
71 71 71.9 71.5 3 2536 214.5 42923.0 0.98332687
72 72 72.9 72.5 2 2538 145.0 43068.0 0.98410237
73 73 73.9 73.5 3 2541 220.5 43288.5 0.98526561
74 74 74.9 74.5 4 2545 298.0 43586.5 0.98681660
75 75 75.9 75.5 3 2548 226.5 43813.0 0.98797984
76 77 77.9 77.5 1 2549 77.5 43890.5 0.98836758
77 79 79.9 79.5 1 2550 79.5 43970.0 0.98875533
78 80 80.9 80.5 2 2552 161.0 44131.0 0.98953083
79 81 81.9 81.5 1 2553 81.5 44212.5 0.98991857
80 82 82.9 82.5 1 2554 82.5 44295.0 0.99030632
81 83 83.9 83.5 2 2556 167.0 44462.0 0.99108181
82 84 84.9 84.5 2 2558 169.0 44631.0 0.99185731
83 85 85.9 85.5 1 2559 85.5 44716.5 0.99224506
84 86 86.9 86.5 2 2561 173.0 44889.5 0.99302055
85 87 87.9 87.5 1 2562 87.5 44977.0 0.99340830
86 90 90.9 90.5 1 2563 90.5 45067.5 0.99379604
87 93 93.9 93.5 2 2565 187.0 45254.5 0.99457154
88 94 94.9 94.5 2 2567 189.0 45443.5 0.99534703
89 96 96.9 96.5 1 2568 96.5 45540.0 0.99573478
90 98 98.9 98.5 1 2569 98.5 45638.5 0.99612253
91 99 99.9 99.5 1 2570 99.5 45738.0 0.99651028
92 103 103.9 103.5 2 2572 207.0 45945.0 0.99728577
93 105 105.9 105.5 1 2573 105.5 46050.5 0.99767352
94 106 106.9 106.5 1 2574 106.5 46157.0 0.99806126
95 107 107.9 107.5 1 2575 107.5 46264.5 0.99844901
96 117 117.9 117.5 1 2576 117.5 46382.0 0.99883676
97 120 120.9 120.5 1 2577 120.5 46502.5 0.99922451
98 150 150.9 150.5 1 2578 150.5 46653.0 0.99961225
99 151 151.9 151.5 1 2579 151.5 46804.5 1.00000000
p.sum.P
1 0.003685543
2 0.011911248
3 0.021557756
4 0.034056554
5 0.050037924
6 0.065869735
7 0.079650461
8 0.097084682
9 0.114946212
10 0.138277302
11 0.158916344
12 0.178412332
13 0.197160529
14 0.217297482
15 0.240810179
16 0.259494279
17 0.280806333
18 0.306498307
19 0.326496384
20 0.349709964
21 0.367624908
22 0.385892382
23 0.405975921
24 0.429531348
25 0.455682680
26 0.469271117
27 0.485722527
28 0.505207833
29 0.518443739
30 0.544509609
31 0.560661902
32 0.572466323
33 0.587496929
34 0.599290666
35 0.620527941
36 0.630665855
37 0.645087545
38 0.659071243
39 0.675949962
40 0.692390689
41 0.709237360
42 0.719225715
43 0.722943307
44 0.736253993
45 0.750835924
46 0.755803395
47 0.764937132
48 0.776335609
49 0.784796334
50 0.800980675
51 0.813084212
52 0.818692647
53 0.827837067
54 0.830165903
55 0.832537470
56 0.838573214
57 0.843487272
58 0.852236430
59 0.861135147
60 0.867598201
61 0.872854106
62 0.876860131
63 0.880930252
64 0.887820616
65 0.892018930
66 0.896281340
67 0.900607848
68 0.903534917
69 0.909474516
70 0.912487047
71 0.917069940
72 0.920167933
73 0.924879018
74 0.931245927
75 0.936085205
76 0.937741029
77 0.939439584
78 0.942879424
79 0.944620710
80 0.946383361
81 0.949951394
82 0.953562157
83 0.955388905
84 0.959085131
85 0.960954609
86 0.962888184
87 0.966883526
88 0.970921599
89 0.972983367
90 0.975087865
91 0.977213729
92 0.981636381
93 0.983890438
94 0.986165860
95 0.988462648
96 0.990973090
97 0.993547629
98 0.996763132
99 1.000000000
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