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This function makes a data table with the result of germination indices for each experimental unit.

Usage

ger_summary(factors, SeedN, evalName, cumulative = FALSE, data)

Arguments

factors

Factor included for the analysis.

SeedN

Name of the column with the seed numbers.

evalName

Prefix of the evaluation variable.

cumulative

Type of data collection [logic: FALSE or TRUE]

data

The name of the data frame containing the data.

Value

Data frame with the summary values of germination variables.

Examples


library(GerminaR)
fb <- prosopis
smr <- ger_summary(factors = c("nacl", "temp", "rep")
                   , SeedN = "seeds"
                   , evalName = "D"
                   , cumulative = FALSE
                   , data = fb)
smr
#>    rep nacl temp seeds grs grp      mgt       mgr       gsp       unc
#> 1    1    0   25    50  50 100 1.280000 0.7812500  78.12500 0.9461447
#> 2    2    0   25    50  50 100 1.220000 0.8196721  81.96721 0.8157272
#> 3    3    0   25    50  50 100 1.320000 0.7575758  75.75758 0.9043815
#> 4    4    0   25    50  50 100 1.140000 0.8771930  87.71930 0.5842388
#> 5    1    0   30    50  50 100 1.040000 0.9615385  96.15385 0.2422922
#> 6    2    0   30    50  50 100 1.060000 0.9433962  94.33962 0.3274449
#> 7    3    0   30    50  50 100 1.000000 1.0000000 100.00000 0.0000000
#> 8    4    0   30    50  50 100 1.020000 0.9803922  98.03922 0.1414405
#> 9    1  0.5   25    50  50 100 1.900000 0.5263158  52.63158 1.0844751
#> 10   2  0.5   25    50  50 100 1.700000 0.5882353  58.82353 1.1985488
#> 11   3  0.5   25    50  50 100 1.880000 0.5319149  53.19149 0.5293609
#> 12   4  0.5   25    50  50 100 1.840000 0.5434783  54.34783 0.6343096
#> 13   1  0.5   30    50  50 100 1.100000 0.9090909  90.90909 0.4689956
#> 14   2  0.5   30    50  50 100 1.160000 0.8620690  86.20690 0.6343096
#> 15   3  0.5   30    50  50 100 1.080000 0.9259259  92.59259 0.4021792
#> 16   4  0.5   30    50  50 100 1.060000 0.9433962  94.33962 0.3274449
#> 17   1    1   25    50  48  96 2.666667 0.3750000  37.50000 1.4171327
#> 18   2    1   25    50  48  96 2.708333 0.3692308  36.92308 1.4081359
#> 19   3    1   25    50  47  94 2.531915 0.3949580  39.49580 1.5822405
#> 20   4    1   25    50  49  98 2.897959 0.3450704  34.50704 1.4950825
#> 21   1    1   30    50  49  98 1.959184 0.5104167  51.04167 0.9281698
#> 22   2    1   30    50  50 100 1.940000 0.5154639  51.54639 0.7050757
#> 23   3    1   30    50  48  96 1.833333 0.5454545  54.54545 0.6500224
#> 24   4    1   30    50  50 100 1.860000 0.5376344  53.76344 0.5842388
#> 25   1  1.5   25    50  47  94 5.382979 0.1857708  18.57708 1.6951591
#> 26   2  1.5   25    50  48  96 5.458333 0.1832061  18.32061 1.8213883
#> 27   3  1.5   25    50  48  96 5.479167 0.1825095  18.25095 1.6026878
#> 28   4  1.5   25    50  49  98 5.448980 0.1835206  18.35206 1.5043742
#> 29   1  1.5   30    50  50 100 3.160000 0.3164557  31.64557 1.5468954
#> 30   2  1.5   30    50  50 100 2.960000 0.3378378  33.78378 1.0302088
#> 31   3  1.5   30    50  50 100 2.900000 0.3448276  34.48276 1.2633065
#> 32   4  1.5   30    50  47  94 2.957447 0.3381295  33.81295 1.0697797
#> 33   1    2   25    50  47  94 6.680851 0.1496815  14.96815 1.6179042
#> 34   2    2   25    50  47  94 6.063830 0.1649123  16.49123 1.9947498
#> 35   3    2   25    50  46  92 6.695652 0.1493506  14.93506 1.9243519
#> 36   4    2   25    50  49  98 6.653061 0.1503067  15.03067 1.5071571
#> 37   1    2   30    50  46  92 4.326087 0.2311558  23.11558 1.2646502
#> 38   2    2   30    50  48  96 4.333333 0.2307692  23.07692 1.3775500
#> 39   3    2   30    50  47  94 4.446809 0.2248804  22.48804 1.6034362
#> 40   4    2   30    50  47  94 4.446809 0.2248804  22.48804 1.9685404
#> 41   1    0   35    50  50 100 1.040000 0.9615385  96.15385 0.2422922
#> 42   2    0   35    50  50 100 1.000000 1.0000000 100.00000 0.0000000
#> 43   3    0   35    50  50 100 1.020000 0.9803922  98.03922 0.1414405
#> 44   4    0   35    50  50 100 1.000000 1.0000000 100.00000 0.0000000
#> 45   1    0   40    50  50 100 1.060000 0.9433962  94.33962 0.3274449
#> 46   2    0   40    50  50 100 1.040000 0.9615385  96.15385 0.2422922
#> 47   3    0   40    50  50 100 1.020000 0.9803922  98.03922 0.1414405
#> 48   4    0   40    50  50 100 1.020000 0.9803922  98.03922 0.1414405
#> 49   1  0.5   35    50  50 100 1.120000 0.8928571  89.28571 0.3274449
#> 50   2  0.5   35    50  48  96 1.062500 0.9411765  94.11765 0.3372901
#> 51   3  0.5   35    50  50 100 1.060000 0.9433962  94.33962 0.2822922
#> 52   4  0.5   35    50  48  96 1.062500 0.9411765  94.11765 0.3372901
#> 53   1  0.5   40    50  48  96 2.333333 0.4285714  42.85714 1.1228074
#> 54   2  0.5   40    50  49  98 2.346939 0.4260870  42.60870 1.3718323
#> 55   3  0.5   40    50  48  96 2.375000 0.4210526  42.10526 1.2987949
#> 56   4  0.5   40    50  47  94 2.255319 0.4433962  44.33962 1.4883676
#> 57   1    1   35    50  49  98 1.653061 0.6049383  60.49383 1.1796780
#> 58   2    1   35    50  48  96 1.729167 0.5783133  57.83133 1.4531143
#> 59   3    1   35    50  46  92 2.173913 0.4600000  46.00000 1.5098718
#> 60   4    1   35    50  49  98 1.714286 0.5833333  58.33333 1.0214779
#> 61   1    1   40    50  50 100 2.940000 0.3401361  34.01361 1.4015264
#> 62   2    1   40    50  48  96 2.520833 0.3966942  39.66942 1.6336284
#> 63   3    1   40    50  49  98 2.714286 0.3684211  36.84211 1.8160410
#> 64   4    1   40    50  50 100 2.740000 0.3649635  36.49635 1.1510457
#> 65   1  1.5   35    50  50 100 3.380000 0.2958580  29.58580 1.7518407
#> 66   2  1.5   35    50  48  96 3.354167 0.2981366  29.81366 1.5487081
#> 67   3  1.5   35    50  50 100 3.360000 0.2976190  29.76190 1.5566689
#> 68   4  1.5   35    50  49  98 3.387755 0.2951807  29.51807 1.6343886
#> 69   1  1.5   40    50   6  12 3.333333 0.3000000  30.00000 1.4591479
#> 70   2  1.5   40    50   6  12 3.166667 0.3157895  31.57895 1.4591479
#> 71   3  1.5   40    50   4   8 3.250000 0.3076923  30.76923 1.5000000
#> 72   4  1.5   40    50   5  10 3.400000 0.2941176  29.41176 1.3709506
#> 73   1    2   35    50  10  20 6.800000 0.1470588  14.70588 2.6464393
#> 74   2    2   35    50  10  20 7.400000 0.1351351  13.51351 1.4854753
#> 75   3    2   35    50   9  18 6.555556 0.1525424  15.25424 1.3516441
#> 76   4    2   35    50  11  22 7.181818 0.1392405  13.92405 2.1626441
#> 77   1    2   40    50   0   0      NaN       NaN       NaN 0.0000000
#> 78   2    2   40    50   0   0      NaN       NaN       NaN 0.0000000
#> 79   3    2   40    50   0   0      NaN       NaN       NaN 0.0000000
#> 80   4    2   40    50   0   0      NaN       NaN       NaN 0.0000000
#>           syn        vgt       sdg      cvg
#> 1  0.63020408 0.32816327 0.5728554 44.75433
#> 2  0.66612245 0.21591837 0.4646702 38.08772
#> 3  0.55591837 0.22204082 0.4712121 35.69788
#> 4  0.75428571 0.12285714 0.3505098 30.74648
#> 5  0.92163265 0.03918367 0.1979487 19.03353
#> 6  0.88489796 0.05755102 0.2398979 22.63188
#> 7  1.00000000 0.00000000 0.0000000  0.00000
#> 8  0.96000000 0.02000000 0.1414214 13.86484
#> 9  0.58122449 0.37755102 0.6144518 32.33957
#> 10 0.48000000 0.37755102 0.6144518 36.14422
#> 11 0.78448980 0.10775510 0.3282607 17.46068
#> 12 0.72571429 0.13714286 0.3703280 20.12652
#> 13 0.81632653 0.09183673 0.3030458 27.54961
#> 14 0.72571429 0.13714286 0.3703280 31.92483
#> 15 0.84979592 0.07510204 0.2740475 25.37477
#> 16 0.88489796 0.05755102 0.2398979 22.63188
#> 17 0.38652482 0.48226950 0.6944563 26.04211
#> 18 0.40514184 0.76418440 0.8741764 32.27728
#> 19 0.39222942 0.86308973 0.9290262 36.69263
#> 20 0.36224490 0.51020408 0.7142857 24.64789
#> 21 0.64795918 0.20663265 0.4545686 23.20194
#> 22 0.74612245 0.13918367 0.3730733 19.23058
#> 23 0.71631206 0.14184397 0.3766218 20.54301
#> 24 0.75428571 0.12285714 0.3505098 18.84461
#> 25 0.30712303 1.71970398 1.3113748 24.36151
#> 26 0.29521277 2.08333333 1.4433757 26.44352
#> 27 0.34485816 2.08466312 1.4438363 26.35138
#> 28 0.35374150 2.21088435 1.4869043 27.28776
#> 29 0.48081633 0.70857143 0.8417668 26.63819
#> 30 0.59918367 0.24326531 0.4932193 16.66282
#> 31 0.50775510 0.37755102 0.6144518 21.18799
#> 32 0.57909343 0.25901943 0.5089395 17.20875
#> 33 0.39037928 0.61332100 0.7831481 11.72228
#> 34 0.26734505 1.06105458 1.0300750 16.98720
#> 35 0.29855072 0.92753623 0.9630868 14.38376
#> 36 0.40816327 0.98129252 0.9906021 14.88942
#> 37 0.44057971 0.35797101 0.5983068 13.83021
#> 38 0.39982270 0.43971631 0.6631111 15.30256
#> 39 0.36077706 0.55689177 0.7462518 16.78174
#> 40 0.28029602 1.03515264 1.0174245 22.87988
#> 41 0.92163265 0.03918367 0.1979487 19.03353
#> 42 1.00000000 0.00000000 0.0000000  0.00000
#> 43 0.96000000 0.02000000 0.1414214 13.86484
#> 44 1.00000000 0.00000000 0.0000000  0.00000
#> 45 0.88489796 0.05755102 0.2398979 22.63188
#> 46 0.92163265 0.03918367 0.1979487 19.03353
#> 47 0.96000000 0.02000000 0.1414214 13.86484
#> 48 0.96000000 0.02000000 0.1414214 13.86484
#> 49 0.88489796 0.23020408 0.4797959 42.83892
#> 50 0.88031915 0.05984043 0.2446230 23.02334
#> 51 0.92081633 0.09836735 0.3136357 29.58827
#> 52 0.88031915 0.05984043 0.2446230 23.02334
#> 53 0.50620567 0.86524823 0.9301872 39.86517
#> 54 0.42517007 0.73129252 0.8551564 36.43710
#> 55 0.45744681 0.75000000 0.8660254 36.46423
#> 56 0.36725254 0.71600370 0.8461700 37.51886
#> 57 0.46768707 0.31462585 0.5609152 33.93191
#> 58 0.37322695 0.49955674 0.7067933 40.87479
#> 59 0.35458937 0.76908213 0.8769733 40.34077
#> 60 0.53826531 0.25000000 0.5000000 29.16667
#> 61 0.47183673 0.46571429 0.6824326 23.21199
#> 62 0.36258865 0.63785461 0.7986580 31.68230
#> 63 0.30527211 0.83333333 0.9128709 33.63209
#> 64 0.59102041 0.48204082 0.6942916 25.33911
#> 65 0.32897959 0.73020408 0.8545198 25.28165
#> 66 0.40780142 0.57402482 0.7576443 22.58815
#> 67 0.37387755 0.52081633 0.7216761 21.47845
#> 68 0.36309524 0.74234694 0.8615956 25.43264
#> 69 0.26666667 0.66666667 0.8164966 24.49490
#> 70 0.26666667 0.96666667 0.9831921 31.04817
#> 71 0.16666667 0.91666667 0.9574271 29.45930
#> 72 0.30000000 0.80000000 0.8944272 26.30668
#> 73 0.08888889 4.84444444 2.2010099 32.36779
#> 74 0.31111111 3.37777778 1.8378732 24.83612
#> 75 0.36111111 3.77777778 1.9436506 29.64891
#> 76 0.16363636 2.76363636 1.6624188 23.14760
#> 77        NaN 0.00000000 0.0000000      NaN
#> 78        NaN 0.00000000 0.0000000      NaN
#> 79        NaN 0.00000000 0.0000000      NaN
#> 80        NaN 0.00000000 0.0000000      NaN