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About 10,000 papers for “Log-log plot”

Log-log survival plot.

Joshua Odunayo Akinyemi (9470978), Rotimi Felix Afolabi (4926022), Olutosin Alaba Awolude (9470981) · Figshare · 2020

Cited by 0Open access

Log-log plot for NPI(3).

Klaus-Jürgen Winzer (427768), Anika Buchholz (2551453), Martin Schumacher (50493) et al. · Figshare · 2016

<p>Log-log plot to check the proportional hazards assumption of the Cox-model for three prognostic groups according to NPI(3).</p>

Cited by 0Open access

Log-Log plot of survival function (CCDF).

Tobias Jordan (3937733), Oto Costa Pinho Alves (3937727), Philippe De Wilde (3937730) et al. · Figshare · 2017

<p>Link-probability related to physical distance between nodes for networks generated with Social Circles (c = 500), Bootstrapping(r = 0.91) and Combined approach (c = 800). Compared to distance- link-probability distributions from real world social networks: Brightkite and Gowalla worldwide networks, as well as local sub networks for the city of New York.</p>

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Plot, log plot, and beyond

Pegg Jr, Ed · Acervo Digital da Universidade Estadual Paulista (Universidade Estadual Paulista) · 2011

Mathematica can plot data in a variety of ways. Eight different plot types are demonstrated here. For some functions, such as (a^x), a log plot is more meaningful than a plot. Hover over a plot to see its Mathematica name

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Plot, Log Plot, and Beyond

Wolfram Demonstrations Project · 2007

Mathematica can plot data in a variety of ways. Eight different plot types are demonstrated here. For some functions, such as a log plot is more meaningful than a plot. Hover over a plot to see its Mathematica name.

Cited by 0Open access

Log-log plot of the whole transcriptome expression analysis.

Marie Schneefeld (4524637), Tobias Busche (3067695), Robert Geffers (23730) et al. · Figshare · 2017

<p>The log-log plot shows the signal intensities of the mutant strain Δ<i>lysG</i> plotted against those of the Wt <i>Mt</i> strain. Spots represent the average of log2 data for each gene from three independent experiments. High through low expression levels are presented as a three-color spectrum. The red color indicates high expression and the green color low expression.</p>

Cited by 0Open access

Log (rank) versus log (frequency) plot for mRNA abundance.

Osamu Ogasawara (3059), Kousaku Okubo (3109) · Figshare · 2015

<p>(A) The mRNA abundance of human (red), mouse (green), chicken (blue), and <i>X. laevis</i> (light blue). (B) Result of the Monte Carlo simulation, <i>L</i> = 0.0. (C) Result of the Monte Carlo simulation, <i>L</i> = 1.0. At the initial state, the mRNA abundance of all genes is set to <i>M</i>/<i>N</i>. Other model parameters of (B) and (C) are: <i>M</i> = 300,000, <i>N</i> = 20,000, and <i>s<sub>k</sub></i> = 0.05. The line shows <i>y</i> = <i>0.1/x</i></p>

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Log-log plot of auto-correlation of turning angles .

Friedrich Lenz (387435), Aleksei V. Chechkin (387436), Rainer Klages (387437) · Figshare · 2015

<p>The experimental data (black crosses) together with an exponential (magenta) and a power-law (blue) fit is shown with the large-lag standard error (grey). The green circles show the auto-correlation extracted from the simulated data.</p>

Cited by 0Open access

Log-log plot of the cumulative distribution of node strength.

Qihui Yang (9213671), Beatriz Martínez-López (402398), Sifat Afroj Moon (8086844) et al. · Figshare · 2025

The blue circles indicate the node strength distribution while the red line is estimated by the linear regression.

Cited by 0Open access

Cluster size distribution of chain-reaction bankruptcies in log-log plot.

Hayato Goto (4488013), Hideki Takayasu (602364), Misako Takayasu (602365) · Figshare · 2017

<p>Black circles show the real distribution from 2006 to 2015. <b>(a)</b> Red triangles and green x-marks show the Monte Carlo simulation results with <i>α</i> = 0.7, <i>β</i> = −0.3 and <i>α</i> = <i>β</i> = 0.0 by 10 attempts, respectively. <b>(b,c)</b> Light blue squares and pink downward triangles show the <b>(b)</b> <i>α</i> = 0.7, <i>β</i> = −0.2 and <i>α</i> = 0.7, <i>β</i> = −0.4, and <b>(c)</b> <i>α</i> = 0.6, <i>β</i> = −0.3 and <i>α</i> = 0.8, <i>β</i> = −0.3 by 10 attempts, respectively. <b>(d)</b> Two-sample Kolmogorov-Smirnov statistical distribution (<i>χ</i><sup>2</sup>) between real and simulated distribution. The smaller the <i>χ</i><sup>2</sup>, the smaller the difference between real and simulated distribution. The cases that take into account of the interaction kernel of chain-reaction bankruptcies (red triangles) fit better with the real data even though the case that ignores the interaction kernel of chain-reaction bankruptcies (green x-marks) is similar to the previous study.</p>

Cited by 0Open access

Cluster size distribution of chain-reaction bankruptcies in log-log plot.

Hayato Goto (4488013), Hideki Takayasu (602364), Misako Takayasu (602365) · Figshare · 2017

<p>Black circles show the real distribution for each year. Red triangles, orange crosses, and pink x-marks show the Monte Carlo simulation results of the best parameters set, the second best parameters set, and the third best parameters set by judging from the median of <i>χ</i><sup>2</sup> of each parameters set by 20 attempts, respectively. <b>(a)</b> <i>α</i> = 0.7, <i>β</i> = −0.3 in 2006. <b>(b)</b> <i>α</i> = 0.8, <i>β</i> = −0.3 in 2007. <b>(c)</b> <i>α</i> = 0.7, <i>β</i> = −0.2 in 2008. <b>(d)</b> <i>α</i> = 0.7, <i>β</i> = −0.4 in 2009. <b>(e)</b> <i>α</i> = 0.7, <i>β</i> = −0.3 in 2010. <b>(f)</b> <i>α</i> = 0.7, <i>β</i> = −0.2 in 2011. <b>(g)</b> <i>α</i> = 0.8, <i>β</i> = −0.3 in 2012. <b>(h)</b> <i>α</i> = 0.8, <i>β</i> = −0.2 in 2013. <b>(i)</b> <i>α</i> = 0.7, <i>β</i> = −0.2 in 2014. <b>(j)</b> <i>α</i> = 0.6, <i>β</i> = −0.2 in 2015. Each <i>α</i> and <i>β</i> of the interaction kernel is positive and negative, respectively, without time variant despite the fact that the number of bankruptcies in Japan has gradually decreased since 2008 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185712#pone.0185712.t001" target="_blank">Table 1</a>.</p>

Cited by 0Open access