describe.augmentedRCBD {augmentedRCBD} R Documentation

## Compute Descriptive Statistics from `augmentedRCBD` Output

### Description

`describe.augmentedRCBD` computes descriptive statistics from the adjusted means in an object of class `augmentedRCBD`.

### Usage

```describe.augmentedRCBD(aug)
```

### Arguments

 `aug` An object of class `augmentedRCBD`.

### Details

`describe.augmentedRCBD` computes the following descriptive statistics from the adjusted means in an object of class `augmentedRCBD`.

• Count

• Mean

• Standard deviation

• Standard error

• Minimum

• Maximum

• Skewness statistic along with p-value from D'Agostino test of skewness (D'Agostino, 1970).

• Kurtosis statistic along with p-value from Anscombe-Glynn test of kurtosis (Anscombe and Glynn, 1983).

### Value

A list with the following descriptive statistics:

 `Count` The number of treatments/genotypes. `Mean` The mean value. `Std.Error` The standard error. `Std.Deviation` The standard deviation. `Min` The minimum value `Max` The maximum value `Skewness(statistic)` The skewness estimator. `Skewness(p.value)` The p-value from D'Agostino test of skewness. `Kurtosis(statistic)` The kurtosis estimator. `Kurtosis(p.value)` The p-value from Anscombe-Glynn test of kurtosis.

### References

D'Agostino RB (1970). “Transformation to normality of the null distribution of g1.” Biometrika, 57(3), 679–681.

Anscombe FJ, Glynn WJ (1983). “Distribution of the kurtosis statistic b2 for normal samples.” Biometrika, 70(1), 227–234.

`augmentedRCBD`

### Examples

```# Example data
blk <- c(rep(1,7),rep(2,6),rep(3,7))
trt <- c(1, 2, 3, 4, 7, 11, 12, 1, 2, 3, 4, 5, 9, 1, 2, 3, 4, 8, 6, 10)
y1 <- c(92, 79, 87, 81, 96, 89, 82, 79, 81, 81, 91, 79, 78, 83, 77, 78, 78,
70, 75, 74)
y2 <- c(258, 224, 238, 278, 347, 300, 289, 260, 220, 237, 227, 281, 311, 250,
240, 268, 287, 226, 395, 450)
data <- data.frame(blk, trt, y1, y2)
# Convert block and treatment to factors
data\$blk <- as.factor(data\$blk)
data\$trt <- as.factor(data\$trt)
# Results for variable y1
out1 <- augmentedRCBD(data\$blk, data\$trt, data\$y1, method.comp = "lsd",
alpha = 0.05, group = TRUE, console = TRUE)
# Results for variable y2
out2 <- augmentedRCBD(data\$blk, data\$trt, data\$y2, method.comp = "lsd",
alpha = 0.05, group = TRUE, console = TRUE)

# Descriptive statistics
describe.augmentedRCBD(out1)
describe.augmentedRCBD(out2)
```

[Package augmentedRCBD version 0.1.5 Index]