43 resultados para Weibull Probability Plot
Resumo:
addplot adds twoway plot objects to an existing twoway graph. This is useful if you want to add additional objects such as titles or extra data points to a twoway graph after it has been created. Most of what addplot can do, can also be done by rerunning the original graph command including additional options or plot statements. addplot, however, might be useful if you have to modify a graph for which you cannot rerun the original command, for example, because you only have the graph file but not the data that were used to create the graph. Furthermore, addplot can do certain things that would be difficult to achieve in a single graph command (e.g. customizing individual subgraphs within a by-graph). addplot also provides a substitute for some of the functionality of the graph editor.
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This article provides an importance sampling algorithm for computing the probability of ruin with recuperation of a spectrally negative Lévy risk process with light-tailed downwards jumps. Ruin with recuperation corresponds to the following double passage event: for some t∈(0,∞)t∈(0,∞), the risk process starting at level x∈[0,∞)x∈[0,∞) falls below the null level during the period [0,t][0,t] and returns above the null level at the end of the period tt. The proposed Monte Carlo estimator is logarithmic efficient, as t,x→∞t,x→∞, when y=t/xy=t/x is constant and below a certain bound.
Resumo:
This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a modified zero-inflated count data model where the probability of an extra zero is derived from an underlying duration model with Weibull hazard rate. The new model is compared to the standard Poisson model with logit zero inflation in an application to the effect of treatment with thiotepa on the number of new bladder tumors.
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A large deviations type approximation to the probability of ruin within a finite time for the compound Poisson risk process perturbed by diffusion is derived. This approximation is based on the saddlepoint method and generalizes the approximation for the non-perturbed risk process by Barndorff-Nielsen and Schmidli (Scand Actuar J 1995(2):169–186, 1995). An importance sampling approximation to this probability of ruin is also provided. Numerical illustrations assess the accuracy of the saddlepoint approximation using importance sampling as a benchmark. The relative deviations between saddlepoint approximation and importance sampling are very small, even for extremely small probabilities of ruin. The saddlepoint approximation is however substantially faster to compute.
Resumo:
OBJECTIVE In patients with a long life expectancy with high-risk (HR) prostate cancer (PCa), the chance to die from PCa is not negligible and may change significantly according to the time elapsed from surgery. The aim of this study was to evaluate long-term survival patterns in young patients treated with radical prostatectomy (RP) for HRPCa. MATERIALS AND METHODS Within a multiinstitutional cohort, 600 young patients (≤59 years) treated with RP between 1987 and 2012 for HRPCa (defined as at least one of the following adverse characteristics: prostate specific antigen>20, cT3 or higher, biopsy Gleason sum 8-10) were identified. Smoothed cumulative incidence plot was performed to assess cancer-specific mortality (CSM) and other cause mortality (OCM) rates at 10, 15, and 20 years after RP. The same analyses were performed to assess the 5-year probability of CSM and OCM in patients who survived 5, 10, and 15 years after RP. A multivariable competing risk regression model was fitted to identify predictors of CSM and OCM. RESULTS The 10-, 15- and 20-year CSM and OCM rates were 11.6% and 5.5% vs. 15.5% and 13.5% vs. 18.4% and 19.3%, respectively. The 5-year probability of CSM and OCM rates among patients who survived at 5, 10, and 15 years after RP, were 6.4% and 2.7% vs. 4.6% and 9.6% vs. 4.2% and 8.2%, respectively. Year of surgery, pathological stage and Gleason score, surgical margin status and lymph node invasion were the major determinants of CSM (all P≤0.03). Conversely, none of the covariates was significantly associated with OCM (all P≥ 0.09). CONCLUSIONS Very long-term cancer control in young high-risk patients after RP is highly satisfactory. The probability of dying from PCa in young patients is the leading cause of death during the first 10 years of survivorship after RP. Thereafter, mortality not related to PCa became the main cause of death. Consequently, surgery should be consider among young patients with high-risk disease and strict PCa follow-up should enforce during the first 10 years of survivorship after RP.
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Although negative density dependence (NDD) can facilitate tree species coexistence in forests, the underlying mechanisms can differ, and rarely are the dynamics of seedlings and saplings studied together. Herein we present and discuss a novel mechanism based on our investigation of NDD predictions for the large, grove-forming ectomycorrhizal mast fruiting tree, Microberlinia bisulcata (Caesalpiniaceae), in an 82.5-ha plot at Korup, Cameroon. We tested whether juvenile density, size, growth and survival decreases with increasing conspecific adult basal area for 3245 ‘new’ seedlings and 540 ‘old’ seedlings (< 75-cm tall) during an approximately 4-year study period (2008–2012) and for 234 ‘saplings’ (≥ 75-cm tall) during an approximately 6-year study period (2008–2014). We found that the respective densities of new seedlings, old seedlings and saplings were positively, not and negatively related to increasing BA. Maximum leaf numbers and heights of old seedlings were negatively correlated with increasing basal areas, as were sapling heights and stem diameters. Whereas survivorship of new seedlings decreased by more than one-half with increasing basal area over its range in 2010–2012, that of old seedlings decreased by almost two-thirds, but only in 2008–2010, and was generally unrelated to conspecific seedling density. In 2010–2012 relative growth rates in new seedlings’ heights decreased with increasing basal area, as well as with increasing seedling density, together with increasing leaf numbers, whereas old seedlings’ growth was unrelated to either conspecific density or basal area. Saplings of below-average height had reduced survivorship with increasing basal area (probability decreasing from approx. 0.4 to 0.05 over the basal area range tested), but only sapling growth in terms of leaf numbers decreased with increasing basal area. These static and dynamic results indicate that NDD is operating within this system, possibly stabilizing the M. bisulcata population. However, these NDD patterns are unlikely to be caused by symmetric competition or by consumers. Instead, an alternative mechanism for conspecific adult–juvenile negative feedback is proposed, one which involves the interaction between tree phenology and ectomycorrhizal linkages.
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logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth
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rrreg fits a linear probability model for randomized response data