Estimation of the Shape Parameter of the Weibull Distribution Using Linear Regression Methods: Non-Censored Samples

The study aims to analyze the influence of internal banking factors in the form of: Capital Adequency Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing at Sharia Banks. This research method used multiple linear regression analysis with the help of SPSS 16.00 software which is used to see the influence between the independent variables in the form of Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing. The sample of this study was 3 Islamic Commercial Banks, so there were 36 annual reports obtained through purposive sampling, then analyzed using multiple linear regression methods. The results showed that based on the F Test, the independent variable had an effect on the NPF, indicated by the F value of 17,016 and significance of 0,000, overall the independent variable was able to explain the effect of 69.60%. While based on the partial t test, showed that CAR has a significant negative effect, Total assets have a significant positive effect with a significance value below 0.05 (5%). Meanwhile FDR does not affect NPF.

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Evaluating the Robustness of UK Term Structure Decompositions Using Linear Regression Methods

SSRN Electronic Journal ◽

10.2139/ssrn.2534455 ◽

2014 ◽

Cited By ~ 2

Author(s):

Sheheryar Malik ◽

Andrew Meldrum

Keyword(s):

Linear Regression ◽

Term Structure ◽

Regression Methods

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Investigation of Feller-Buncher Performance Using Weibull Distribution

Forests ◽

10.3390/f12030284 ◽

2021 ◽

Vol 12 (3) ◽

pp. 284

Author(s):

Ebru Bilici

Keyword(s):

Weibull Distribution ◽

Shape Parameter ◽

B Value ◽

Productivity Analysis ◽

Volume Data ◽

Estimation Model ◽

Distribution Method ◽

Timber Volume ◽

C Value ◽

The Right

With the advancement of technology in forestry, the utilization of advanced machines in forest operations has been increasing in the last decades. Due to their high operating costs, it is crucial to select the right machinery, which is mostly done by using productivity analysis. In this study, a productivity estimation model was developed in order to determine the timber volume cut per unit time for a feller-buncher. The Weibull distribution method was used to develop the productivity model. In the study, the model of the theoretical (estimated) volume distributions obtained with the Weibull probability density function was generated. It was found that the c value was 1.96 and the b value was 0.58 (i.e., b is the scale parameter, and c is the shape parameter). The model indicated that the frequency of the volume data had moved away from 0 as the shape parameter of the Weibull distribution increased. Thus, it was revealed that the shape parameter gives preliminary information about the distribution of the volume frequency. The consistency of the measured timber volume with the estimated timber volume strongly indicated that this approach can be effectively used by decision makers as a key tool to predict the productivity of a feller-buncher used in harvesting operations.

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Generating a Baseline Map of Surface Fuel Loading Using Stratified Random Sampling Inventory Data through Cokriging and Multiple Linear Regression Methods

Remote Sensing ◽

10.3390/rs13081561 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1561

Author(s):

Chinsu Lin ◽

Siao-En Ma ◽

Li-Ping Huang ◽

Chung-I Chen ◽

Pei-Ting Lin ◽

...

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Random Sampling ◽

Fuel Load ◽

Estimation Accuracy ◽

Slope Aspect ◽

Stratified Random Sampling ◽

Inventory Data ◽

Fuel Loading ◽

Regression Methods

Surface fuel loading is a key factor in controlling wildfires and planning sustainable forest management. Spatially explicit maps of surface fuel loading can highlight the risks of a forest fire. Geospatial information is critical in enabling careful use of deliberate fire setting and also helps to minimize the possibility of heat conduction over forest lands. In contrast to lidar sensing and/or optical sensing based methods, an approach of integrating in-situ fuel inventory data, geospatial interpolation techniques, and multiple linear regression methods provides an alternative approach to surface fuel load estimation and mapping over mountainous forests. Using a stratified random sampling based inventory and cokriging analysis, surface fuel loading data of 120 plots distributed over four kinds of fuel types were collected in order to develop a total surface fuel loading model (lntSFL-BioTopo model) and a fine surface fuel model (lnfSFL-BioTopo model) for generating tSFL and fSFL maps. Results showed that the combination of topographic parameters such as slope, aspect, and their cross products and the fuel types such as pine stand, non-pine conifer stand, broadleaf stand, and conifer–broadleaf mixed stand was able to appropriately describe the changes in surface fuel loads over a forest with diverse terrain morphology. Based on a cross-validation method, the estimation of tSFL and fSFL of the study site had an RMSE of 3.476 tons/ha and 3.384 tons/ha, respectively. In contrast to the average loading of all inventory plots, the estimation for tSFL and fSFL had a relative error of 38% (PRMSE). The reciprocal of estimation bias of both SFL-BioTopo models tended to be an exponential growth function of the amount of surface fuel load, indicating that the estimation accuracy of the proposed method is likely to be improved with further study. In the regression modeling, a natural logarithm transformation of the surface fuel loading prevented the outcome of negative estimates and thus improved the estimation. Based on the results, this paper defined a minimum sampling unit (MSU) as the area for collecting surface fuels for interpolation using a cokriging model. Allocating the MSUs at the boundary and center of a plot improved surface fuel load prediction and mapping.

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Estimation of constant-stress accelerated life test for Weibull distribution with nonconstant shape parameter

Journal of Computational and Applied Mathematics ◽

10.1016/j.cam.2018.05.012 ◽

2018 ◽

Vol 343 ◽

pp. 539-555 ◽

Cited By ~ 4

Author(s):

Liang Wang

Keyword(s):

Weibull Distribution ◽

Shape Parameter ◽

Constant Stress ◽

Accelerated Life Test ◽

Life Test ◽

Accelerated Life

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Study on Sequential Compliance Method Influenced by Shape Parameter of Weibull Distribution

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.189-193.4361 ◽

2011 ◽

Vol 189-193 ◽

pp. 4361-4364 ◽

Cited By ~ 1

Author(s):

Hong Liang Lou ◽

Xing Lin Li ◽

Xian Zhao Xu ◽

Yang Ping Zhang ◽

Zhong Hua Yu

Keyword(s):

Weibull Distribution ◽

Shape Parameter ◽

Weibull Distributions ◽

Simulation Test ◽

Consumer’S Risk ◽

Producer’S Risk ◽

Rejection Probability

When sequential compliance method is used for Weibull distributions, the shape parameter is usually considered to be fixed. However, because of the life of products are determined by many factors, the shape parameter is variational in practice, that is to say, the shape parameter in the criterions is different from that in the practice. In this paper, the changes of acceptance and rejection probability are researched by the influence of shape parameter changes. Finally, by means of simulation test, changes on the shape parameter affecting on the probability of acceptance and rejection are quantitatively analyzed. As a result, the larger the gap on the shape parameter in the criterions and in the practice is, the larger the gap on the producer’s risk and the consumer’s risk.

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