repl.txt (4160B)
1 2 {{alias}}( N, mean, correction, x, stride ) 3 Computes the variance of a double-precision floating-point strided array 4 provided a known mean and using Neely's correction algorithm. 5 6 The `N` and `stride` parameters determine which elements in `x` are accessed 7 at runtime. 8 9 Indexing is relative to the first index. To introduce an offset, use a typed 10 array view. 11 12 If `N <= 0`, the function returns `NaN`. 13 14 Parameters 15 ---------- 16 N: integer 17 Number of indexed elements. 18 19 mean: number 20 Mean. 21 22 correction: number 23 Degrees of freedom adjustment. Setting this parameter to a value other 24 than `0` has the effect of adjusting the divisor during the calculation 25 of the variance according to `N - c` where `c` corresponds to the 26 provided degrees of freedom adjustment. When computing the variance of a 27 population, setting this parameter to `0` is the standard choice (i.e., 28 the provided array contains data constituting an entire population). 29 When computing the unbiased sample variance, setting this parameter to 30 `1` is the standard choice (i.e., the provided array contains data 31 sampled from a larger population; this is commonly referred to as 32 Bessel's correction). 33 34 x: Float64Array 35 Input array. 36 37 stride: integer 38 Index increment. 39 40 Returns 41 ------- 42 out: number 43 The variance. 44 45 Examples 46 -------- 47 // Standard Usage: 48 > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); 49 > {{alias}}( x.length, 1.0/3.0, 1, x, 1 ) 50 ~4.3333 51 52 // Using `N` and `stride` parameters: 53 > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); 54 > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 55 > {{alias}}( N, 1.0/3.0, 1, x, 2 ) 56 ~4.3333 57 58 // Using view offsets: 59 > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] ); 60 > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); 61 > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); 62 > {{alias}}( N, 1.0/3.0, 1, x1, 2 ) 63 ~4.3333 64 65 {{alias}}.ndarray( N, mean, correction, x, stride, offset ) 66 Computes the variance of a double-precision floating-point strided array 67 provided a known mean and using Neely's correction algorithm and alternative 68 indexing semantics. 69 70 While typed array views mandate a view offset based on the underlying 71 buffer, the `offset` parameter supports indexing semantics based on a 72 starting index. 73 74 Parameters 75 ---------- 76 N: integer 77 Number of indexed elements. 78 79 mean: number 80 Mean. 81 82 correction: number 83 Degrees of freedom adjustment. Setting this parameter to a value other 84 than `0` has the effect of adjusting the divisor during the calculation 85 of the variance according to `N - c` where `c` corresponds to the 86 provided degrees of freedom adjustment. When computing the variance of a 87 population, setting this parameter to `0` is the standard choice (i.e., 88 the provided array contains data constituting an entire population). 89 When computing the unbiased sample variance, setting this parameter to 90 `1` is the standard choice (i.e., the provided array contains data 91 sampled from a larger population; this is commonly referred to as 92 Bessel's correction). 93 94 x: Float64Array 95 Input array. 96 97 stride: integer 98 Index increment. 99 100 offset: integer 101 Starting index. 102 103 Returns 104 ------- 105 out: number 106 The variance. 107 108 Examples 109 -------- 110 // Standard Usage: 111 > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); 112 > {{alias}}.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 ) 113 ~4.3333 114 115 // Using offset parameter: 116 > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] ); 117 > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 118 > {{alias}}.ndarray( N, 1.0/3.0, 1, x, 2, 1 ) 119 ~4.3333 120 121 See Also 122 -------- 123