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Apply a function on each pair of features

Usage

pairwiseApply(X, ...)

Arguments

X

input object

...

additional arguments

Value

a list containing the output of applying the function to each feature pair. See ?base::mapply()

Examples

web <- randomWeb(10)

# For each feature pair, was the value for x higher than the value for y?
pairwiseApply(
    X = web,
    FUN = function(x, y) x > y,
    MoreArgs = NULL, SIMPLIFY = FALSE, USE.NAMES = TRUE
    )
#> $x_1y_1
#>  [1] FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_1y_2
#>  [1] FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE
#> 
#> $x_1y_3
#>  [1] FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE  TRUE
#> 
#> $x_1y_4
#>  [1] FALSE  TRUE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE
#> 
#> $x_1y_5
#>  [1] FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_1y_6
#>  [1] FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE FALSE
#> 
#> $x_1y_7
#>  [1] FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE
#> 
#> $x_1y_10
#>  [1] FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_1y_11
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE FALSE FALSE
#> 
#> $x_1y_12
#>  [1] FALSE  TRUE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE
#> 
#> $x_2y_1
#>  [1]  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_2y_5
#>  [1] FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE
#> 
#> $x_2y_7
#>  [1] FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE FALSE  TRUE  TRUE
#> 
#> $x_2y_9
#>  [1]  TRUE  TRUE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE  TRUE
#> 
#> $x_3y_5
#>  [1] FALSE  TRUE  TRUE FALSE FALSE  TRUE FALSE  TRUE  TRUE FALSE
#> 
#> $x_3y_6
#>  [1] FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE FALSE
#> 
#> $x_3y_7
#>  [1] FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE
#> 
#> $x_3y_8
#>  [1] FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE  TRUE  TRUE
#> 
#> $x_3y_10
#>  [1] FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_3y_11
#>  [1] FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_4y_3
#>  [1] FALSE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_4y_4
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE
#> 
#> $x_4y_5
#>  [1] FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_4y_6
#>  [1] FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_4y_7
#>  [1] FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_4y_9
#>  [1]  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE FALSE  TRUE  TRUE
#> 
#> $x_4y_10
#>  [1] FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_4y_11
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_5y_3
#>  [1] FALSE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_5y_5
#>  [1] FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE FALSE
#> 
#> $x_5y_6
#>  [1] FALSE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
#> 
#> $x_5y_9
#>  [1]  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE
#> 
#> $x_5y_11
#>  [1] FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_5y_12
#>  [1] FALSE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE
#> 
#> $x_6y_2
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE
#> 
#> $x_6y_4
#>  [1] FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_6y_5
#>  [1] FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_6y_7
#>  [1] FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_6y_8
#>  [1] FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE
#> 
#> $x_6y_11
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_7y_1
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_7y_3
#>  [1] FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE
#> 
#> $x_7y_4
#>  [1]  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE
#> 
#> $x_7y_5
#>  [1] FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE
#> 
#> $x_7y_7
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_7y_9
#>  [1]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE
#> 
#> $x_7y_11
#>  [1] FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE
#> 
#> $x_8y_7
#>  [1] FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE
#> 

# Run cor.test() on each pair of features
pairwiseApply(
    X = web,
    FUN = function(x, y) cor.test(x, y),
    MoreArgs = NULL, SIMPLIFY = FALSE, USE.NAMES = TRUE
)
#> $x_1y_1
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.2123, df = 8, p-value = 0.26
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.3134075  0.8201495
#> sample estimates:
#>       cor 
#> 0.3939584 
#> 
#> 
#> $x_1y_2
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.52621, df = 8, p-value = 0.613
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5048631  0.7286213
#> sample estimates:
#>       cor 
#> 0.1829038 
#> 
#> 
#> $x_1y_3
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.36517, df = 8, p-value = 0.7244
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7011451  0.5455645
#> sample estimates:
#>        cor 
#> -0.1280458 
#> 
#> 
#> $x_1y_4
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.19595, df = 8, p-value = 0.8495
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5860147  0.6696007
#> sample estimates:
#>        cor 
#> 0.06911177 
#> 
#> 
#> $x_1y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.2863, df = 8, p-value = 0.2343
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.2916716  0.8278300
#> sample estimates:
#>       cor 
#> 0.4139796 
#> 
#> 
#> $x_1y_6
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.672, df = 8, p-value = 0.1331
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8622416  0.1776704
#> sample estimates:
#>        cor 
#> -0.5088825 
#> 
#> 
#> $x_1y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.51762, df = 8, p-value = 0.6187
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7272171  0.5070852
#> sample estimates:
#>        cor 
#> -0.1800154 
#> 
#> 
#> $x_1y_10
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.027191, df = 8, p-value = 0.979
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6237889  0.6353935
#> sample estimates:
#>        cor 
#> 0.00961297 
#> 
#> 
#> $x_1y_11
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.025948, df = 8, p-value = 0.9799
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6240572  0.6351315
#> sample estimates:
#>         cor 
#> 0.009173661 
#> 
#> 
#> $x_1y_12
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.26934, df = 8, p-value = 0.7945
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6836208  0.5687771
#> sample estimates:
#>         cor 
#> -0.09479795 
#> 
#> 
#> $x_2y_1
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.131, df = 8, p-value = 0.2908
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.3371720  0.8112571
#> sample estimates:
#>       cor 
#> 0.3712727 
#> 
#> 
#> $x_2y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.27357, df = 8, p-value = 0.7913
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5677696  0.6844126
#> sample estimates:
#>        cor 
#> 0.09627242 
#> 
#> 
#> $x_2y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.75683, df = 8, p-value = 0.4709
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4432842  0.7638038
#> sample estimates:
#>       cor 
#> 0.2584866 
#> 
#> 
#> $x_2y_9
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.64565, df = 8, p-value = 0.5366
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7474405  0.4734153
#> sample estimates:
#>        cor 
#> -0.2225464 
#> 
#> 
#> $x_3y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.0356, df = 8, p-value = 0.3307
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.3647586  0.8002221
#> sample estimates:
#>       cor 
#> 0.3438329 
#> 
#> 
#> $x_3y_6
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.36525, df = 8, p-value = 0.7244
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5455462  0.7011583
#> sample estimates:
#>       cor 
#> 0.1280714 
#> 
#> 
#> $x_3y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.12593, df = 8, p-value = 0.9029
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6020062  0.6557415
#> sample estimates:
#>        cor 
#> 0.04447966 
#> 
#> 
#> $x_3y_8
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.10064, df = 8, p-value = 0.9223
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6076714  0.6506196
#> sample estimates:
#>        cor 
#> 0.03556058 
#> 
#> 
#> $x_3y_10
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.226, df = 8, p-value = 0.2551
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8215959  0.3094028
#> sample estimates:
#>        cor 
#> -0.3976984 
#> 
#> 
#> $x_3y_11
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.1428, df = 8, p-value = 0.2862
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.3337125  0.8125854
#> sample estimates:
#>       cor 
#> 0.3746285 
#> 
#> 
#> $x_4y_3
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.60543, df = 8, p-value = 0.5617
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7412488  0.4841173
#> sample estimates:
#>        cor 
#> -0.2093091 
#> 
#> 
#> $x_4y_4
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.2468, df = 8, p-value = 0.2477
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.3032866  0.8237773
#> sample estimates:
#>       cor 
#> 0.4033652 
#> 
#> 
#> $x_4y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -2.4507, df = 8, p-value = 0.03989
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.90948113 -0.04289438
#> sample estimates:
#>        cor 
#> -0.6548353 
#> 
#> 
#> $x_4y_6
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.67516, df = 8, p-value = 0.5186
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7518916  0.4654927
#> sample estimates:
#>        cor 
#> -0.2321834 
#> 
#> 
#> $x_4y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.26053, df = 8, p-value = 0.801
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5708718  0.6819650
#> sample estimates:
#>       cor 
#> 0.0917231 
#> 
#> 
#> $x_4y_9
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.35945, df = 8, p-value = 0.7286
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5469720  0.7001237
#> sample estimates:
#>       cor 
#> 0.1260719 
#> 
#> 
#> $x_4y_10
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.9028, df = 8, p-value = 0.09357
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8789159  0.1101624
#> sample estimates:
#>        cor 
#> -0.5581799 
#> 
#> 
#> $x_4y_11
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.58023, df = 8, p-value = 0.5777
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4907642  0.7372953
#> sample estimates:
#>       cor 
#> 0.2009576 
#> 
#> 
#> $x_5y_3
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.0385, df = 8, p-value = 0.3294
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.3639343  0.8005637
#> sample estimates:
#>       cor 
#> 0.3446707 
#> 
#> 
#> $x_5y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.4494, df = 8, p-value = 0.1853
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8434813  0.2434854
#> sample estimates:
#>        cor 
#> -0.4560566 
#> 
#> 
#> $x_5y_6
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.4162, df = 8, p-value = 0.1944
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8404338  0.2533082
#> sample estimates:
#>        cor 
#> -0.4477257 
#> 
#> 
#> $x_5y_9
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.58271, df = 8, p-value = 0.5761
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4901126  0.7376866
#> sample estimates:
#>       cor 
#> 0.2017808 
#> 
#> 
#> $x_5y_11
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.033809, df = 8, p-value = 0.9739
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6223575  0.6367865
#> sample estimates:
#>        cor 
#> 0.01195242 
#> 
#> 
#> $x_5y_12
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.20726, df = 8, p-value = 0.841
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.5833898  0.6717950
#> sample estimates:
#>        cor 
#> 0.07308018 
#> 
#> 
#> $x_6y_2
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.091373, df = 8, p-value = 0.9294
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6097336  0.6487263
#> sample estimates:
#>        cor 
#> 0.03228832 
#> 
#> 
#> $x_6y_4
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.73967, df = 8, p-value = 0.4806
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4479839  0.7613498
#> sample estimates:
#>       cor 
#> 0.2530059 
#> 
#> 
#> $x_6y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.2316, df = 8, p-value = 0.2531
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8221858  0.3077581
#> sample estimates:
#>        cor 
#> -0.3992276 
#> 
#> 
#> $x_6y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.4067, df = 8, p-value = 0.1972
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8395424  0.2561394
#> sample estimates:
#>        cor 
#> -0.4453016 
#> 
#> 
#> $x_6y_8
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.82321, df = 8, p-value = 0.4342
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4249411  0.7730594
#> sample estimates:
#>       cor 
#> 0.2794544 
#> 
#> 
#> $x_6y_11
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.4496, df = 8, p-value = 0.1852
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8434979  0.2434311
#> sample estimates:
#>        cor 
#> -0.4561023 
#> 
#> 
#> $x_7y_1
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.60281, df = 8, p-value = 0.5633
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4848093  0.7408412
#> sample estimates:
#>       cor 
#> 0.2084444 
#> 
#> 
#> $x_7y_3
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 0.72119, df = 8, p-value = 0.4913
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.4530277  0.7586769
#> sample estimates:
#>       cor 
#> 0.2470734 
#> 
#> 
#> $x_7y_4
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.7753, df = 8, p-value = 0.4605
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7664173  0.4382052
#> sample estimates:
#>        cor 
#> -0.2643593 
#> 
#> 
#> $x_7y_5
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.64978, df = 8, p-value = 0.534
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.7480676  0.4723110
#> sample estimates:
#>       cor 
#> -0.223898 
#> 
#> 
#> $x_7y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.1092, df = 8, p-value = 0.2996
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8087934  0.3435069
#> sample estimates:
#>       cor 
#> -0.365079 
#> 
#> 
#> $x_7y_9
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = 1.4186, df = 8, p-value = 0.1938
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.252606  0.840654
#> sample estimates:
#>       cor 
#> 0.4483253 
#> 
#> 
#> $x_7y_11
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -1.5589, df = 8, p-value = 0.1576
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.8530650  0.2110694
#> sample estimates:
#>       cor 
#> -0.482706 
#> 
#> 
#> $x_8y_7
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  x and y
#> t = -0.21526, df = 8, p-value = 0.835
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.6733402  0.5815256
#> sample estimates:
#>         cor 
#> -0.07588588 
#> 
#>