Boris Iglewicz
Datos Biográficos
| ID | 10705709 |
|---|---|
| NOMBRE | Boris Iglewicz |
| NOMBRES | Boris |
| APELLIDO | Iglewicz |
| FIRMA | IGLEWICZ B |
| AFILIACIONES | Temple University |
| VERIFICADO | No |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 1986 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 1987 |
| ÍNDICE H | 0 |
Fine-Tuning Some Resistant Rules for Outlier Labeling
A previous study examined the performance of a standard rule from Exploratory Data Analysis, which uses the sample fourths, FL and FU , and labels as “outside” any observations below FL – k(FU – FL ) or above FU + k(FU – FL ), customarily with k = 1.5. In terms of the order statistics X (1) ≤ X (2) ≤ X (n) the standard definition of the fourths is FL = X(f) and FU = X (n + 1 − f), where f = 1⁄2[(n + 3)/2] and [·] denotes the greatest-integer func…
Performance of Some Resistant Rules for Outlier Labeling
The techniques of exploratory data analysis include a resistant rule for identifying possible outliers in univariate data. Using the lower and upper fourths, FL and FU (approximate quartiles), it labels as “outside” any observations below FL − 1.5(FU — FL ) or above FU + 1.5(FU — FL ). For example, in the ordered sample −5, −2, 0, 1, 8, FL = −2 and FU = 1, so any observation below −6.5 or above 5.5 is outside. Thus the rule labels 8 as outside. S…
Sin obras prominentes en esta página.
Performance of Some Resistant Rules for Outlier Labeling
The techniques of exploratory data analysis include a resistant rule for identifying possible outliers in univariate data. Using the lower and upper fourths, FL and FU (approximate quartiles), it labels as “outside” any observations below FL − 1.5(FU — FL ) or above FU + 1.5(FU — FL ). For example, in the ordered sample −5, −2, 0, 1, 8, FL = −2 and FU = 1, so any observation below −6.5 or above 5.5 is outside. Thus the rule labels 8 as outside. S…
Fine-Tuning Some Resistant Rules for Outlier Labeling
A previous study examined the performance of a standard rule from Exploratory Data Analysis, which uses the sample fourths, FL and FU , and labels as “outside” any observations below FL – k(FU – FL ) or above FU + k(FU – FL ), customarily with k = 1.5. In terms of the order statistics X (1) ≤ X (2) ≤ X (n) the standard definition of the fourths is FL = X(f) and FU = X (n + 1 − f), where f = 1⁄2[(n + 3)/2] and [·] denotes the greatest-integer func…
Advanced Statistical Methods and Models (2 obras) · Advanced Statistical Process Monitoring (2 obras) · Computer Science (2 obras) · Mathematics (2 obras) · Outlier (2 obras) · Statistics (2 obras) · Artificial Intelligence (1 obras) · Combinatorics (1 obras) · Estimator (1 obras) · Function (biology) (1 obras)