ライフサイエンスコーパス: jackknife

1 k-fold cross-validation, bootstrapping, and jackknifing.

2 a prediction rule that was evaluated through jackknifing.

3 espective confidence limits are estimated by jackknifing.

4 built from the full alignment and from each jackknifed alignment, and then the likelihood for each t

5 LumberJack creates non-random jackknifed alignments by progressively sliding a window

6 aracteristic analysis was performed by using jackknife alternative free-response receiver operating c

7 correctly classified 72% of participants in jackknife analyses.

8 Jackknife analysis of CAC results in the training data s

9 Jackknife analysis provided estimates of statistical sig

10 We implemented a jackknife analysis to identify those species most influe

11 Jackknife analysis was used for prediction of probabilit

12 LDA jackknife analysis, a statistical resampling technique,

13 d to standard resampling methodology such as jackknifing and noise perturbation.

14 Results obtained through re-substitution, jackknife, and independent data set tests, respectively,

15 Instead, a leave-data-out jackknife approach better estimates the influence of a g

16 en when 35% of the data were left out in the jackknife approach, the confidence levels of SHAPE-direc

17 pean, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversit

18 to the quality of input according to a novel jackknife confidence scoring.

19 (1) intragroup pattern uniformity by use of jackknife correlation coefficient analysis of the integr

20 s evident between the two automated systems (jackknife correlation r = PL 0.77 [95% confidence interv

21 ntal observed and predicted folding rates in jackknife cross validation.

22 e power was assessed using a "leave one out" jackknife cross-validation strategy.

23 nD-PseAA predictor on such a data set by the jackknife cross-validation test was 85% for the case in

24 f iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmar

25 With a combination of 6 variables, a jackknifed cross-validation test found the probability o

26 normally distributed and admits a consistent jackknife estimator of its variance.

27 using the Flury hierarchical method and the jackknife followed by MANOVA method.

28 The jackknife free-response receiver operating characteristi

29 A jackknifing free response operating characteristic (JAFR

30 r Min proteins induced frequent and dramatic jackknife-like bending of cells at division septa, with

31 analysis can be done using the data from the jackknife method but the estimated power is typically a

32 SPLUS coding for the implementation of the jackknife method is provided.

33 A jackknife method was used because any patient may have m

34 The jackknife method was used for bias correction.

35 g characteristic (ROC) analysis by using the jackknife method.

36 ors such as Capture recapture, Chao, ACE and Jackknife methods.

37 We present a jackknife model for ligase III that posits conformationa

38 The collective results support a "jackknife model" in which the ZnF loads ligase III onto

39 ion through the variance estimator using the jackknife, one of resampling techniques.

40 trocar technique with the patient in a prone jackknife position.

41 he paired sire and dam pseudovalues from the jackknife procedure and the likelihood ratio test from t

42 Logistic regression and the jackknife procedure were used to select correlates of on

43 rametric resampling method, an index (called jackknifed reliability index, JRI) was proposed, and emp

44 SEs and 95% CIs were assessed by using jackknife replicate weights.

45 of serum analyte by using sample weights and jackknife replication methods to adjust for the complex

46 s remained largely unchanged in quartile and jackknife sensitivity analyses.

47 iring adjustment as in Efron (2004) or using jackknife standard errors.

48 ernal validity of the predictive gene set, a jackknife step is used.

49 It is shown by the self-consistency test, jackknife test and independent dataset tests that the su

50 The success rate by jackknife test for the 139 serine hydrolases was 85%, im

51 The overall success rate by the jackknife test for the identification between enzyme and

52 The overall success rate of the jackknife test for the plant protein dataset was 86%, an

53 It is observed in the jackknife test that the accuracy achieved by the propose

54 L (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminate

55 s are obtained by the self-consistency test, jackknife test, and independent dataset test, respective

56 In a jackknife test, EFICAz shows high accuracy (92%) and sen

57 cleotide composition were 80-90% accurate in jackknife testing experiments for bacteria and 90-99% fo

58 -based potentials is evaluated by using four jackknife tests and by assessing the potentials' ability

59 re obtained by both the self-consistency and jackknife tests.

60 sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss